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1. Reverse-Engineering the Reader

Author

Kiegeland, Samuel, Wilcox, Ethan Gotlieb, Amini, Afra, Reich, David Robert, and Cotterell, Ryan

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Numerous previous studies have sought to determine to what extent language models, pretrained on natural language text, can serve as useful models of human cognition. In this paper, we are interested in the opposite question: whether we can directly optimize a language model to be a useful cognitive model by aligning it to human psychometric data. To achieve this, we introduce a novel alignment technique in which we fine-tune a language model to implicitly optimize the parameters of a linear regressor that directly predicts humans' reading times of in-context linguistic units, e.g., phonemes, morphemes, or words, using surprisal estimates derived from the language model. Using words as a test case, we evaluate our technique across multiple model sizes and datasets and find that it improves language models' psychometric predictive power. However, we find an inverse relationship between psychometric power and a model's performance on downstream NLP tasks as well as its perplexity on held-out test data. While this latter trend has been observed before (Oh et al., 2022; Shain et al., 2024), we are the first to induce it by manipulating a model's alignment to psychometric data.

Published
2024

2. EMTeC: A Corpus of Eye Movements on Machine-Generated Texts

Author

Bolliger, Lena Sophia, Haller, Patrick, Cretton, Isabelle Caroline Rose, Reich, David Robert, Kew, Tannon, and Jäger, Lena Ann

Subjects
Computer Science - Computation and Language
Abstract

The Eye Movements on Machine-Generated Texts Corpus (EMTeC) is a naturalistic eye-movements-while-reading corpus of 107 native English speakers reading machine-generated texts. The texts are generated by three large language models using five different decoding strategies, and they fall into six different text type categories. EMTeC entails the eye movement data at all stages of pre-processing, i.e., the raw coordinate data sampled at 2000 Hz, the fixation sequences, and the reading measures. It further provides both the original and a corrected version of the fixation sequences, accounting for vertical calibration drift. Moreover, the corpus includes the language models' internals that underlie the generation of the stimulus texts: the transition scores, the attention scores, and the hidden states. The stimuli are annotated for a range of linguistic features both at text and at word level. We anticipate EMTeC to be utilized for a variety of use cases such as, but not restricted to, the investigation of reading behavior on machine-generated text and the impact of different decoding strategies; reading behavior on different text types; the development of new pre-processing, data filtering, and drift correction algorithms; the cognitive interpretability and enhancement of language models; and the assessment of the predictive power of surprisal and entropy for human reading times. The data at all stages of pre-processing, the model internals, and the code to reproduce the stimulus generation, data pre-processing and analyses can be accessed via https://github.com/DiLi-Lab/EMTeC/.

Published
2024

3. Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Author

Hirten, Robert P, Danieletto, Matteo, Tomalin, Lewis, Choi, Katie Hyewon, Zweig, Micol, Golden, Eddye, Kaur, Sparshdeep, Helmus, Drew, Biello, Anthony, Pyzik, Renata, Charney, Alexander, Miotto, Riccardo, Glicksberg, Benjamin S, Levin, Matthew, Nabeel, Ismail, Aberg, Judith, Reich, David, Charney, Dennis, Bottinger, Erwin P, Keefer, Laurie, Suarez-Farinas, Mayte, Nadkarni, Girish N, and Fayad, Zahi A

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundChanges in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. ObjectiveWe performed an evaluation of HRV collected by a wearable device to identify and predict COVID-19 and its related symptoms. MethodsHealth care workers in the Mount Sinai Health System were prospectively followed in an ongoing observational study using the custom Warrior Watch Study app, which was downloaded to their smartphones. Participants wore an Apple Watch for the duration of the study, measuring HRV throughout the follow-up period. Surveys assessing infection and symptom-related questions were obtained daily. ResultsUsing a mixed-effect cosinor model, the mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats (SDNN), an HRV metric, differed between subjects with and without COVID-19 (P=.006). The mean amplitude of this circadian pattern differed between individuals during the 7 days before and the 7 days after a COVID-19 diagnosis compared to this metric during uninfected time periods (P=.01). Significant changes in the mean and amplitude of the circadian pattern of the SDNN was observed between the first day of reporting a COVID-19–related symptom compared to all other symptom-free days (P=.01). ConclusionsLongitudinally collected HRV metrics from a commonly worn commercial wearable device (Apple Watch) can predict the diagnosis of COVID-19 and identify COVID-19–related symptoms. Prior to the diagnosis of COVID-19 by nasal swab polymerase chain reaction testing, significant changes in HRV were observed, demonstrating the predictive ability of this metric to identify COVID-19 infection.

Published
2021
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4. Social and genetic diversity in first farmers of central Europe

Author

Gelabert, Pere, Bickle, Penny, Hofmann, Daniela, Teschler-Nicola, Maria, Anders, Alexandra, Huang, Xin, Hämmerle, Michelle, Olalde, Iñigo, Fournier, Romain, Ringbauer, Harald, Akbari, Ali, Cheronet, Olivia, Lazaridis, Iosif, Broomandkhoshbacht, Nasreen, Fernandes, Daniel M., Buttinger, Katharina, Callan, Kim, Candilio, Francesca, Bravo Morante, Guillermo, Curtis, Elizabeth, Ferry, Matthew, Keating, Denise, Freilich, Suzanne, Kearns, Aisling, Harney, Éadaoin, Lawson, Ann Marie, Mandl, Kirsten, Michel, Megan, Oberreiter, Victoria, Zagorc, Brina, Oppenheimer, Jonas, Sawyer, Susanna, Schattke, Constanze, Özdoğan, Kadir Toykan, Qiu, Lijun, Workman, J. Noah, Zalzala, Fatma, Mallick, Swapan, Mah, Matthew, Micco, Adam, Pieler, Franz, Pavuk, Juraj, Šefčáková, Alena, Lazar, Catalin, Starović, Andrej, Djuric, Marija, Krznarić Škrivanko, Maja, Šlaus, Mario, Bedić, Željka, Novotny, Friederike, D. Szabó, László, Cserpák-Laczi, Orsolya, Hága, Tamara, Szolnoki, László, Hajdú, Zsigmond, Mirea, Pavel, Nagy, Emese Gyöngyvér, Virág, Zsuzsanna M., Horváth M., Attila, Horváth, László András, T. Biró, Katalin, Domboróczki, László, Szeniczey, Tamás, Jakucs, János, Szelekovszky, Márta, Zoltán, Farkas, Sztáncsuj, Sándor József, Tóth, Krisztián, Csengeri, Piroska, Pap, Ildikó, Patay, Róbert, Putica, Anđelka, Vasov, Branislav, Havasi, Bálint, Sebők, Katalin, Raczky, Pál, Lovász, Gabriella, Tvrdý, Zdeněk, Rohland, Nadin, Novak, Mario, Ruttkay, Matej, Krošláková, Maria, Bátora, Jozef, Paluch, Tibor, Borić, Dušan, Dani, János, Kuhlwilm, Martin, Palamara, Pier Francesco, Hajdu, Tamás, Pinhasi, Ron, and Reich, David

Published
2024
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5. Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Author

Vaid, Akhil, Somani, Sulaiman, Russak, Adam J, De Freitas, Jessica K, Chaudhry, Fayzan F, Paranjpe, Ishan, Johnson, Kipp W, Lee, Samuel J, Miotto, Riccardo, Richter, Felix, Zhao, Shan, Beckmann, Noam D, Naik, Nidhi, Kia, Arash, Timsina, Prem, Lala, Anuradha, Paranjpe, Manish, Golden, Eddye, Danieletto, Matteo, Singh, Manbir, Meyer, Dara, O'Reilly, Paul F, Huckins, Laura, Kovatch, Patricia, Finkelstein, Joseph, Freeman, Robert M., Argulian, Edgar, Kasarskis, Andrew, Percha, Bethany, Aberg, Judith A, Bagiella, Emilia, Horowitz, Carol R, Murphy, Barbara, Nestler, Eric J, Schadt, Eric E, Cho, Judy H, Cordon-Cardo, Carlos, Fuster, Valentin, Charney, Dennis S, Reich, David L, Bottinger, Erwin P, Levin, Matthew A, Narula, Jagat, Fayad, Zahi A, Just, Allan C, Charney, Alexander W, Nadkarni, Girish N, and Glicksberg, Benjamin S

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundCOVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. ObjectiveThe aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. MethodsWe used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19–positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. ResultsUpon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. ConclusionsWe externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Published
2020
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6. PoTeC: A German Naturalistic Eye-tracking-while-reading Corpus

Author

Jakobi, Deborah N., Kern, Thomas, Reich, David R., Haller, Patrick, and Jäger, Lena A.

Subjects
Computer Science - Computation and Language
Abstract

The Potsdam Textbook Corpus (PoTeC) is a naturalistic eye-tracking-while-reading corpus containing data from 75 participants reading 12 scientific texts. PoTeC is the first naturalistic eye-tracking-while-reading corpus that contains eye-movements from domain-experts as well as novices in a within-participant manipulation: It is based on a 2x2x2 fully-crossed factorial design which includes the participants' level of study and the participants' discipline of study as between-subject factors and the text domain as a within-subject factor. The participants' reading comprehension was assessed by a series of text comprehension questions and their domain knowledge was tested by text-independent background questions for each of the texts. The materials are annotated for a variety of linguistic features at different levels. We envision PoTeC to be used for a wide range of studies including but not limited to analyses of expert and non-expert reading strategies. The corpus and all the accompanying data at all stages of the preprocessing pipeline and all code used to preprocess the data are made available via GitHub: https://github.com/DiLi-Lab/PoTeC.

Published
2024

7. Natural Language Programming in Medicine: Administering Evidence Based Clinical Workflows with Autonomous Agents Powered by Generative Large Language Models

Author

Vaid, Akhil, Lampert, Joshua, Lee, Juhee, Sawant, Ashwin, Apakama, Donald, Sakhuja, Ankit, Soroush, Ali, Bick, Sarah, Abbott, Ethan, Gomez, Hernando, Hadley, Michael, Lee, Denise, Landi, Isotta, Duong, Son Q, Bussola, Nicole, Nabeel, Ismail, Muehlstedt, Silke, Freeman, Robert, Kovatch, Patricia, Carr, Brendan, Wang, Fei, Glicksberg, Benjamin, Argulian, Edgar, Lerakis, Stamatios, Khera, Rohan, Reich, David L., Kraft, Monica, Charney, Alexander, and Nadkarni, Girish

Subjects
Computer Science - Artificial Intelligence
Abstract

Generative Large Language Models (LLMs) hold significant promise in healthcare, demonstrating capabilities such as passing medical licensing exams and providing clinical knowledge. However, their current use as information retrieval tools is limited by challenges like data staleness, resource demands, and occasional generation of incorrect information. This study assessed the potential of LLMs to function as autonomous agents in a simulated tertiary care medical center, using real-world clinical cases across multiple specialties. Both proprietary and open-source LLMs were evaluated, with Retrieval Augmented Generation (RAG) enhancing contextual relevance. Proprietary models, particularly GPT-4, generally outperformed open-source models, showing improved guideline adherence and more accurate responses with RAG. The manual evaluation by expert clinicians was crucial in validating models' outputs, underscoring the importance of human oversight in LLM operation. Further, the study emphasizes Natural Language Programming (NLP) as the appropriate paradigm for modifying model behavior, allowing for precise adjustments through tailored prompts and real-world interactions. This approach highlights the potential of LLMs to significantly enhance and supplement clinical decision-making, while also emphasizing the value of continuous expert involvement and the flexibility of NLP to ensure their reliability and effectiveness in healthcare settings., Comment: Figures: 5, Tables: 3

Published
2024

8. An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets

Author

Gulamali, Faris F., Sawant, Ashwin S., Liharska, Lora, Horowitz, Carol R., Chan, Lili, Kovatch, Patricia H., Hofer, Ira, Singh, Karandeep, Richardson, Lynne D., Mensah, Emmanuel, Charney, Alexander W, Reich, David L., Hu, Jianying, and Nadkarni, Girish N.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

The adoption of diagnosis and prognostic algorithms in healthcare has led to concerns about the perpetuation of bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around modifying models, optimization strategies, and threshold calibration with varying levels of success. Here, we generate a data-centric, model-agnostic, task-agnostic approach to evaluate dataset bias by investigating the relationship between how easily different groups are learned at small sample sizes (AEquity). We then apply a systematic analysis of AEq values across subpopulations to identify and mitigate manifestations of racial bias in two known cases in healthcare - Chest X-rays diagnosis with deep convolutional neural networks and healthcare utilization prediction with multivariate logistic regression. AEq is a novel and broadly applicable metric that can be applied to advance equity by diagnosing and remediating bias in healthcare datasets.

Published
2023

9. ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts

Author

Bolliger, Lena S., Reich, David R., Haller, Patrick, Jakobi, Deborah N., Prasse, Paul, and Jäger, Lena A.

Subjects
Computer Science - Computation and Language
Abstract

Eye movements in reading play a crucial role in psycholinguistic research studying the cognitive mechanisms underlying human language processing. More recently, the tight coupling between eye movements and cognition has also been leveraged for language-related machine learning tasks such as the interpretability, enhancement, and pre-training of language models, as well as the inference of reader- and text-specific properties. However, scarcity of eye movement data and its unavailability at application time poses a major challenge for this line of research. Initially, this problem was tackled by resorting to cognitive models for synthesizing eye movement data. However, for the sole purpose of generating human-like scanpaths, purely data-driven machine-learning-based methods have proven to be more suitable. Following recent advances in adapting diffusion processes to discrete data, we propose ScanDL, a novel discrete sequence-to-sequence diffusion model that generates synthetic scanpaths on texts. By leveraging pre-trained word representations and jointly embedding both the stimulus text and the fixation sequence, our model captures multi-modal interactions between the two inputs. We evaluate ScanDL within- and across-dataset and demonstrate that it significantly outperforms state-of-the-art scanpath generation methods. Finally, we provide an extensive psycholinguistic analysis that underlines the model's ability to exhibit human-like reading behavior. Our implementation is made available at https://github.com/DiLi-Lab/ScanDL., Comment: EMNLP 2023

Published
2023

10. Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding

Author

Deng, Shuwen, Prasse, Paul, Reich, David R., Scheffer, Tobias, and Jäger, Lena A.

Subjects
Computer Science - Computation and Language
Abstract

Human gaze data offer cognitive information that reflects natural language comprehension. Indeed, augmenting language models with human scanpaths has proven beneficial for a range of NLP tasks, including language understanding. However, the applicability of this approach is hampered because the abundance of text corpora is contrasted by a scarcity of gaze data. Although models for the generation of human-like scanpaths during reading have been developed, the potential of synthetic gaze data across NLP tasks remains largely unexplored. We develop a model that integrates synthetic scanpath generation with a scanpath-augmented language model, eliminating the need for human gaze data. Since the model's error gradient can be propagated throughout all parts of the model, the scanpath generator can be fine-tuned to downstream tasks. We find that the proposed model not only outperforms the underlying language model, but achieves a performance that is comparable to a language model augmented with real human gaze data. Our code is publicly available., Comment: Pre-print for EMNLP 2023

Published
2023

12. Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension

Author

Gulamali, Faris, Jayaraman, Pushkala, Sawant, Ashwin S., Desman, Jacob, Fox, Benjamin, Chang, Annette, Soong, Brian Y., Arivazagan, Naveen, Reynolds, Alexandra S., Duong, Son Q., Vaid, Akhil, Kovatch, Patricia, Freeman, Robert, Hofer, Ira S., Sakhuja, Ankit, Dangayach, Neha S., Reich, David S., Charney, Alexander W., and Nadkarni, Girish N.

Published
2024
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14. Medieval DNA from Soqotra points to Eurasian origins of an isolated population at the crossroads of Africa and Arabia

Author

Sirak, Kendra, Jansen Van Rensburg, Julian, Brielle, Esther, Chen, Bowen, Lazaridis, Iosif, Ringbauer, Harald, Mah, Matthew, Mallick, Swapan, Micco, Adam, Rohland, Nadin, Callan, Kimberly, Curtis, Elizabeth, Kearns, Aisling, Lawson, Ann Marie, Workman, J. Noah, Zalzala, Fatma, Ahmed Al-Orqbi, Ahmed Saeed, Ahmed Salem, Esmail Mohammed, Salem Hasan, Ali Mohammed, Britton, Daniel Charles, and Reich, David

Published
2024
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15. Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading

Author

Deng, Shuwen, Reich, David R., Prasse, Paul, Haller, Patrick, Scheffer, Tobias, and Jäger, Lena A.

Subjects
Computer Science - Computation and Language, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract

Eye movements during reading offer insights into both the reader's cognitive processes and the characteristics of the text that is being read. Hence, the analysis of scanpaths in reading have attracted increasing attention across fields, ranging from cognitive science over linguistics to computer science. In particular, eye-tracking-while-reading data has been argued to bear the potential to make machine-learning-based language models exhibit a more human-like linguistic behavior. However, one of the main challenges in modeling human scanpaths in reading is their dual-sequence nature: the words are ordered following the grammatical rules of the language, whereas the fixations are chronologically ordered. As humans do not strictly read from left-to-right, but rather skip or refixate words and regress to previous words, the alignment of the linguistic and the temporal sequence is non-trivial. In this paper, we develop Eyettention, the first dual-sequence model that simultaneously processes the sequence of words and the chronological sequence of fixations. The alignment of the two sequences is achieved by a cross-sequence attention mechanism. We show that Eyettention outperforms state-of-the-art models in predicting scanpaths. We provide an extensive within- and across-data set evaluation on different languages. An ablation study and qualitative analysis support an in-depth understanding of the model's behavior.

Published
2023

16. Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models

Author

Krakowczyk, Daniel G., Prasse, Paul, Reich, David R., Lapuschkin, Sebastian, Scheffer, Tobias, and Jäger, Lena A.

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction
Abstract

Recent work in XAI for eye tracking data has evaluated the suitability of feature attribution methods to explain the output of deep neural sequence models for the task of oculomotric biometric identification. These methods provide saliency maps to highlight important input features of a specific eye gaze sequence. However, to date, its localization analysis has been lacking a quantitative approach across entire datasets. In this work, we employ established gaze event detection algorithms for fixations and saccades and quantitatively evaluate the impact of these events by determining their concept influence. Input features that belong to saccades are shown to be substantially more important than features that belong to fixations. By dissecting saccade events into sub-events, we are able to show that gaze samples that are close to the saccadic peak velocity are most influential. We further investigate the effect of event properties like saccadic amplitude or fixational dispersion on the resulting concept influence., Comment: Preprint for ETRA '23: 2023 Symposium on Eye Tracking Research and Applications

Published
2023
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17. pymovements: A Python Package for Eye Movement Data Processing

Author

Krakowczyk, Daniel G., Reich, David R., Chwastek, Jakob, Jakobi, Deborah N., Prasse, Paul, Süss, Assunta, Turuta, Oleksii, Kasprowski, Paweł, and Jäger, Lena A.

Subjects
Computer Science - Human-Computer Interaction, 91, J.4
Abstract

We introduce pymovements: a Python package for analyzing eye-tracking data that follows best practices in software development, including rigorous testing and adherence to coding standards. The package provides functionality for key processes along the entire preprocessing pipeline. This includes parsing of eye tracker data files, transforming positional data into velocity data, detecting gaze events like saccades and fixations, computing event properties like saccade amplitude and fixational dispersion and visualizing data and results with several types of plotting methods. Moreover, pymovements also provides an easily accessible interface for downloading and processing publicly available datasets. Additionally, we emphasize how rigorous testing in scientific software packages is critical to the reproducibility and transparency of research, enabling other researchers to verify and build upon previous findings., Comment: Preprint for ETRA '23: 2023 Symposium on Eye Tracking Research and Applications

Published
2023
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19. Identifying Personal Identifiable Information (PII) in Unstructured Text: A Comparative Study on Transformers

Author

Shahriar, Md Hasan, Kayem, Anne V. D. M., Reich, David, Meinel, Christoph, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Strauss, Christine, editor, Amagasa, Toshiyuki, editor, Manco, Giuseppe, editor, Kotsis, Gabriele, editor, Tjoa, A Min, editor, and Khalil, Ismail, editor

Published
2024
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21. Detection of ADHD based on Eye Movements during Natural Viewing

Author

Deng, Shuwen, Prasse, Paul, Reich, David R., Dziemian, Sabine, Stegenwallner-Schütz, Maja, Krakowczyk, Daniel, Makowski, Silvia, Langer, Nicolas, Scheffer, Tobias, and Jäger, Lena A.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is highly prevalent and requires clinical specialists to diagnose. It is known that an individual's viewing behavior, reflected in their eye movements, is directly related to attentional mechanisms and higher-order cognitive processes. We therefore explore whether ADHD can be detected based on recorded eye movements together with information about the video stimulus in a free-viewing task. To this end, we develop an end-to-end deep learning-based sequence model which we pre-train on a related task for which more data are available. We find that the method is in fact able to detect ADHD and outperforms relevant baselines. We investigate the relevance of the input features in an ablation study. Interestingly, we find that the model's performance is closely related to the content of the video, which provides insights for future experimental designs., Comment: Pre-print for Proceedings of the European Conference on Machine Learning, 2022

Published
2022

22. Author Correction: Genetic continuity and change among the Indigenous peoples of California

Author

Nakatsuka, Nathan, Holguin, Brian, Sedig, Jakob, Langenwalter, II, Paul E., Carpenter, John, Culleton, Brendan J., García-Moreno, Cristina, Harper, Thomas K., Martin, Debra, Martínez-Ramírez, Júpiter, Porcayo-Michelini, Antonio, Tiesler, Vera, Villapando-Canchola, M. Elisa, Valdes Herrera, Alejandro, Callan, Kim, Curtis, Elizabeth, Kearns, Aisling, Iliev, Lora, Lawson, Ann Marie, Mah, Matthew, Mallick, Swapan, Micco, Adam, Michel, Megan, Workman, J. Noah, Oppenheimer, Jonas, Qiu, Lijun, Zalzala, Fatma, Rohland, Nadin, Punzo Diaz, Jose Luis, Johnson, John R., and Reich, David

Published
2024
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24. Genetic continuity and change among the Indigenous peoples of California

Author

Nakatsuka, Nathan, Holguin, Brian, Sedig, Jakob, Langenwalter, II, Paul E., Carpenter, John, Culleton, Brendan J., García-Moreno, Cristina, Harper, Thomas K., Martin, Debra, Martínez-Ramírez, Júpiter, Porcayo-Michelini, Antonio, Tiesler, Vera, Villapando-Canchola, M. Elisa, Valdes Herrera, Alejandro, Callan, Kim, Curtis, Elizabeth, Kearns, Aisling, Iliev, Lora, Lawson, Ann Marie, Mah, Matthew, Mallick, Swapan, Micco, Adam, Michel, Megan, Workman, J. Noah, Oppenheimer, Jonas, Qiu, Lijun, Zalzala, Fatma, Rohland, Nadin, Punzo Diaz, Jose Luis, Johnson, John R., and Reich, David

Published
2023
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29. Detection of ADHD Based on Eye Movements During Natural Viewing

Author

Deng, Shuwen, Prasse, Paul, Reich, David R., Dziemian, Sabine, Stegenwallner-Schütz, Maja, Krakowczyk, Daniel, Makowski, Silvia, Langer, Nicolas, Scheffer, Tobias, Jäger, Lena A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Amini, Massih-Reza, editor, Canu, Stéphane, editor, Fischer, Asja, editor, Guns, Tias, editor, Kralj Novak, Petra, editor, and Tsoumakas, Grigorios, editor

Published
2023
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30. Ethics of DNA research on human remains: five globally applicable guidelines

Author

Alpaslan-Roodenberg, Songül, Anthony, David, Babiker, Hiba, Bánffy, Eszter, Booth, Thomas, Capone, Patricia, Deshpande-Mukherjee, Arati, Eisenmann, Stefanie, Fehren-Schmitz, Lars, Frachetti, Michael, Fujita, Ricardo, Frieman, Catherine J, Fu, Qiaomei, Gibbon, Victoria, Haak, Wolfgang, Hajdinjak, Mateja, Hofmann, Kerstin P, Holguin, Brian, Inomata, Takeshi, Kanzawa-Kiriyama, Hideaki, Keegan, William, Kelso, Janet, Krause, Johannes, Kumaresan, Ganesan, Kusimba, Chapurukha, Kusimba, Sibel, Lalueza-Fox, Carles, Llamas, Bastien, MacEachern, Scott, Mallick, Swapan, Matsumura, Hirofumi, Morales-Arce, Ana Y, Matuzeviciute, Giedre Motuzaite, Mushrif-Tripathy, Veena, Nakatsuka, Nathan, Nores, Rodrigo, Ogola, Christine, Okumura, Mercedes, Patterson, Nick, Pinhasi, Ron, Prasad, Samayamantri PR, Prendergast, Mary E, Punzo, Jose Luis, Reich, David, Sawafuji, Rikai, Sawchuk, Elizabeth, Schiffels, Stephan, Sedig, Jakob, Shnaider, Svetlana, Sirak, Kendra, Skoglund, Pontus, Slon, Viviane, Snow, Meradeth, Soressi, Marie, Spriggs, Matthew, Stockhammer, Philipp W, Szécsényi-Nagy, Anna, Thangaraj, Kumarasamy, Tiesler, Vera, Tobler, Ray, Wang, Chuan-Chao, Warinner, Christina, Yasawardene, Surangi, and Zahir, Muhammad

Subjects
Human Genome, Genetics, Generic health relevance, American Indian or Alaska Native, Anthropology, Archaeology, Cadaver, Community-Institutional Relations, DNA, Ancient, Guidelines as Topic, Human Genetics, Humans, Indigenous Peoples, Internationality, Molecular Biology, Stakeholder Participation, Translations, General Science & Technology
Abstract

We are a group of archaeologists, anthropologists, curators and geneticists representing diverse global communities and 31 countries. All of us met in a virtual workshop dedicated to ethics in ancient DNA research held in November 2020. There was widespread agreement that globally applicable ethical guidelines are needed, but that recent recommendations grounded in discussion about research on human remains from North America are not always generalizable worldwide. Here we propose the following globally applicable guidelines, taking into consideration diverse contexts. These hold that: (1) researchers must ensure that all regulations were followed in the places where they work and from which the human remains derived; (2) researchers must prepare a detailed plan prior to beginning any study; (3) researchers must minimize damage to human remains; (4) researchers must ensure that data are made available following publication to allow critical re-examination of scientific findings; and (5) researchers must engage with other stakeholders from the beginning of a study and ensure respect and sensitivity to stakeholder perspectives. We commit to adhering to these guidelines and expect they will promote a high ethical standard in DNA research on human remains going forward.

Published
2021

31. Kinship practices in Early Iron Age South-east Europe: genetic and isotopic analysis of burials from the Dolge njive barrow cemetery, Dolenjska, Slovenia

Author

Armit, Ian, Fischer, Claire-Elise, Koon, Hannah, Nicholls, Rebecca, Olalde, Inigo, Rohland, Nadin, Buckberry, Jo, Montgomery, Janet, Mason, Philip, Cresnar, Matija, Buster, Lindsey, and Reich, David

Subjects
Anthropological research, Cemeteries -- Discovery and exploration, Kinship -- Analysis, Burial -- Analysis, Anthropology/archeology/folklore
Abstract

The burial of multiple individuals within a single funerary monument invites speculation about the relationships between the deceased: were they chosen on the basis of status, gender or relatedness, for example? Here, the authors present the results of aDNA and isotope analyses conducted on seven individuals from an Early Iron Age barrow at Dolge njive, south-eastern Slovenia. All seven individuals are close biological relatives. While the group composition suggests strict adherence to neither patrilineal nor matrilineal structures, the funerary tradition appears highly gendered, and family links through both the male and female lines seem important in structuring of the community. The results have implications for understanding of kinship and funerary practices in late prehistoric Europe. Keywords: Slovenia, Iron Age, genetic sequencing, funerary archaeology, isotope analysis, social organisation, Introduction The beginning of the Early Iron Age (c. 800--450 BC) in South-east Europe was characterised by a number of significant social changes. In many cases, these developments appear to [...]

Published
2023
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33. Ancient mitochondrial genomes from the Argentinian Pampas inform the early peopling of the Southern Cone of South America

Author

Roca-Rada, Xavier, Politis, Gustavo, Messineo, Pablo G, Scheifler, Nahuel, Scabuzzo, Clara, González, Mariela, Harkins, Kelly M, Reich, David, Souilmi, Yassine, Teixeira, João C, Llamas, Bastien, and Fehren-Schmitz, Lars

Subjects
Biological Sciences, Anthropology, Genetics, Human Society, Genomics, Paleogenetics
Abstract

The Southern Cone of South America (SCSA) is a key region for investigations about the peopling of the Americas. However, little is known about the eastern sector, the Argentinian Pampas. We analyzed 18 mitochondrial genomes-7 of which are novel-from human skeletal remains from 3 Early to Late Holocene archaeological sites. The Pampas present a distinctive genetic makeup compared to other Middle to Late Holocene pre-Columbian SCSA populations. We also report the earliest individuals carrying SCSA-specific mitochondrial haplogroups D1j and D1g from Early and Middle Holocene, respectively. Using these deep calibration time points in Bayesian phylogenetic reconstructions, we suggest that the first settlers of the Pampas were part of a single and rapid dispersal ∼15,600 years ago. Finally, we propose that present-day genetic differences between the Pampas and the rest of the SCSA are due to founder effects, genetic drift, and a partial population replacement ∼9,000 years ago.

Published
2021

34. A genetic history of the Balkans from Roman frontier to Slavic migrations

Author

Olalde, Iñigo, Carrión, Pablo, Mikić, Ilija, Rohland, Nadin, Mallick, Swapan, Lazaridis, Iosif, Mah, Matthew, Korać, Miomir, Golubović, Snežana, Petković, Sofija, Miladinović-Radmilović, Nataša, Vulović, Dragana, Alihodžić, Timka, Ash, Abigail, Baeta, Miriam, Bartík, Juraj, Bedić, Željka, Bilić, Maja, Bonsall, Clive, Bunčić, Maja, Bužanić, Domagoj, Carić, Mario, Čataj, Lea, Cvetko, Mirna, Drnić, Ivan, Dugonjić, Anita, Đukić, Ana, Đukić, Ksenija, Farkaš, Zdeněk, Jelínek, Pavol, Jovanovic, Marija, Kaić, Iva, Kalafatić, Hrvoje, Krmpotić, Marijana, Krznar, Siniša, Leleković, Tino, M. de Pancorbo, Marian, Matijević, Vinka, Milošević Zakić, Branka, Osterholtz, Anna J., Paige, Julianne M., Tresić Pavičić, Dinko, Premužić, Zrinka, Rajić Šikanjić, Petra, Rapan Papeša, Anita, Paraman, Lujana, Sanader, Mirjana, Radovanović, Ivana, Roksandic, Mirjana, Šefčáková, Alena, Stefanović, Sofia, Teschler-Nicola, Maria, Tončinić, Domagoj, Zagorc, Brina, Callan, Kim, Candilio, Francesca, Cheronet, Olivia, Fernandes, Daniel, Kearns, Aisling, Lawson, Ann Marie, Mandl, Kirsten, Wagner, Anna, Zalzala, Fatma, Zettl, Anna, Tomanović, Željko, Keckarević, Dušan, Novak, Mario, Harper, Kyle, McCormick, Michael, Pinhasi, Ron, Grbić, Miodrag, Lalueza-Fox, Carles, and Reich, David

Published
2023
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35. Entwined African and Asian genetic roots of medieval peoples of the Swahili coast

Author

Brielle, Esther S., Fleisher, Jeffrey, Wynne-Jones, Stephanie, Sirak, Kendra, Broomandkhoshbacht, Nasreen, Callan, Kim, Curtis, Elizabeth, Iliev, Lora, Lawson, Ann Marie, Oppenheimer, Jonas, Qiu, Lijun, Stewardson, Kristin, Workman, J. Noah, Zalzala, Fatma, Ayodo, George, Gidna, Agness O., Kabiru, Angela, Kwekason, Amandus, Mabulla, Audax Z. P., Manthi, Fredrick K., Ndiema, Emmanuel, Ogola, Christine, Sawchuk, Elizabeth, Al-Gazali, Lihadh, Ali, Bassam R., Ben-Salem, Salma, Letellier, Thierry, Pierron, Denis, Radimilahy, Chantal, Rakotoarisoa, Jean-Aimé, Raaum, Ryan L., Culleton, Brendan J., Mallick, Swapan, Rohland, Nadin, Patterson, Nick, Mwenje, Mohammed Ali, Ahmed, Khalfan Bini, Mohamed, Mohamed Mchulla, Williams, Sloan R., Monge, Janet, Kusimba, Sibel, Prendergast, Mary E., Reich, David, and Kusimba, Chapurukha M.

Published
2023
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37. Two genetic variants explain the association of European ancestry with multiple sclerosis risk in African-Americans.

Author

Nakatsuka, Nathan, Patterson, Nick, Patsopoulos, Nikolaos A, Altemose, Nicolas, Tandon, Arti, Beecham, Ashley H, McCauley, Jacob L, Isobe, Noriko, Hauser, Stephen, De Jager, Philip L, Hafler, David A, Oksenberg, Jorge R, and Reich, David

Subjects
Humans, Multiple Sclerosis, Genetic Predisposition to Disease, Odds Ratio, Haplotypes, Polymorphism, Single Nucleotide, African Americans, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study
Abstract

Epidemiological studies have suggested differences in the rate of multiple sclerosis (MS) in individuals of European ancestry compared to African ancestry, motivating genetic scans to identify variants that could contribute to such patterns. In a whole-genome scan in 899 African-American cases and 1155 African-American controls, we confirm that African-Americans who inherit segments of the genome of European ancestry at a chromosome 1 locus are at increased risk for MS [logarithm of odds (LOD) = 9.8], although the signal weakens when adding an additional 406 cases, reflecting heterogeneity in the two sets of cases [logarithm of odds (LOD) = 2.7]. The association in the 899 individuals can be fully explained by two variants previously associated with MS in European ancestry individuals. These variants tag a MS susceptibility haplotype associated with decreased CD58 gene expression (odds ratio of 1.37; frequency of 84% in Europeans and 22% in West Africans for the tagging variant) as well as another haplotype near the FCRL3 gene (odds ratio of 1.07; frequency of 49% in Europeans and 8% in West Africans). Controlling for all other genetic and environmental factors, the two variants predict a 1.44-fold higher rate of MS in European-Americans compared to African-Americans.

Published
2020

38. Increased rate of close-kin unions in the central Andes in the half millennium before European contact

Author

Ringbauer, Harald, Steinrücken, Matthias, Fehren-Schmitz, Lars, and Reich, David

Subjects
Biological Sciences, Genetics, DNA, Ancient, History, Ancient, History, Medieval, Humans, Inbreeding, Reproduction, South America, Medical and Health Sciences, Psychology and Cognitive Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences, Psychology
Abstract

Analyzing ancient DNA of the central Andes, Ringbauer and colleagues identify a markedly elevated rate of unions of closely related parents after ca. 1000 CE. This change of mating preferences sheds new light on a unique system of social organization based on ancestry ("ayllu") whereby within-group unions were preferred to facilitate sharing of resources.

Published
2020

40. The Anglo-Saxon migration and the formation of the early English gene pool

Author

Gretzinger, Joscha, Sayer, Duncan, Justeau, Pierre, Altena, Eveline, Pala, Maria, Dulias, Katharina, Edwards, Ceiridwen J., Jodoin, Susanne, Lacher, Laura, Sabin, Susanna, Vågene, Åshild J., Haak, Wolfgang, Ebenesersdóttir, S. Sunna, Moore, Kristjan H. S., Radzeviciute, Rita, Schmidt, Kara, Brace, Selina, Bager, Martina Abenhus, Patterson, Nick, Papac, Luka, Broomandkhoshbacht, Nasreen, Callan, Kimberly, Harney, Éadaoin, Iliev, Lora, Lawson, Ann Marie, Michel, Megan, Stewardson, Kristin, Zalzala, Fatma, Rohland, Nadin, Kappelhoff-Beckmann, Stefanie, Both, Frank, Winger, Daniel, Neumann, Daniel, Saalow, Lars, Krabath, Stefan, Beckett, Sophie, Van Twest, Melanie, Faulkner, Neil, Read, Chris, Barton, Tabatha, Caruth, Joanna, Hines, John, Krause-Kyora, Ben, Warnke, Ursula, Schuenemann, Verena J., Barnes, Ian, Dahlström, Hanna, Clausen, Jane Jark, Richardson, Andrew, Popescu, Elizabeth, Dodwell, Natasha, Ladd, Stuart, Phillips, Tom, Mortimer, Richard, Sayer, Faye, Swales, Diana, Stewart, Allison, Powlesland, Dominic, Kenyon, Robert, Ladle, Lilian, Peek, Christina, Grefen-Peters, Silke, Ponce, Paola, Daniels, Robin, Spall, Cecily, Woolcock, Jennifer, Jones, Andy M., Roberts, Amy V., Symmons, Robert, Rawden, Anooshka C., Cooper, Alan, Bos, Kirsten I., Booth, Tom, Schroeder, Hannes, Thomas, Mark G., Helgason, Agnar, Richards, Martin B., Reich, David, Krause, Johannes, and Schiffels, Stephan

Published
2022
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42. Genomic Analysis of the Individuals from El Mirador Cave

Author

Olalde, Iñigo, Lalueza-Fox, Carles, Reich, David, Eerkens, Jelmer, Series Editor, Çakırlar, Canan, Editorial Board Member, Iizuka, Fumie, Editorial Board Member, Seetah, Krish, Editorial Board Member, Sugranes, Nuria, Editorial Board Member, Tushingham, Shannon, Editorial Board Member, Wilson, Chris, Editorial Board Member, Allué, Ethel, editor, Martín, Patricia, editor, and Vergès, Josep Maria, editor

Published
2022
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43. Life and death in early colonial Campeche: new insights from ancient DNA

Author

Tiesler, Vera, Sedig, Jakob, Nakatsuka, Nathan, Mallick, Swapan, Lazaridis, Iosif, Bernardos, Rebecca, Broomandkhoshbacht, Nasreen, Oppenheimer, Jonas, Lawson, Ann Marie, Stewardson, Kristin, Rohland, Nadin, Kennett, Douglas J., Price, T. Douglas, and Reich, David

Subjects
Anthropological research, Cemeteries -- Discovery and exploration, Multiculturalism -- Analysis, Colonial cities -- Research, DNA testing, Anthropology/archeology/folklore
Abstract

Campeche, one of the Spanish Empire's main Mexican ports, was a place where previously distinct cultures and populations intermingled during the colonial era (AD 1540-1680). Investigation of the town's central plaza revealed a Hispanic cemetery of multi-ethnic burials. The authors combine previous analyses with newly generated genome-wide data from 10 individuals to trace detailed life histories of the mostly young, local Indigenous Americans and first-generation European and African immigrants, none of whom show evidence of genetic admixture. These results provide insights into the individual lives and social divides of the town's founder communities and demonstrate how ancient DNA analyses can contribute to understanding early colonial encounters. Keywords: Mexico, Campeche, Novohispanic society, ancient DNA, isotope analysis, genomics, Introduction Following their arrival in 1519, the Spanish conquistadors took less than two years to conquer Aztec central Mexico; however, it took a further two decades to secure their rule [...]

Published
2022
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45. Ancient DNA and deep population structure in sub-Saharan African foragers

Author

Lipson, Mark, Sawchuk, Elizabeth A., Thompson, Jessica C., Oppenheimer, Jonas, Tryon, Christian A., Ranhorn, Kathryn L., de Luna, Kathryn M., Sirak, Kendra A., Olalde, Iñigo, Ambrose, Stanley H., Arthur, John W., Arthur, Kathryn J. W., Ayodo, George, Bertacchi, Alex, Cerezo-Román, Jessica I., Culleton, Brendan J., Curtis, Matthew C., Davis, Jacob, Gidna, Agness O., Hanson, Annalys, Kaliba, Potiphar, Katongo, Maggie, Kwekason, Amandus, Laird, Myra F., Lewis, Jason, Mabulla, Audax Z. P., Mapemba, Fredrick, Morris, Alan, Mudenda, George, Mwafulirwa, Raphael, Mwangomba, Daudi, Ndiema, Emmanuel, Ogola, Christine, Schilt, Flora, Willoughby, Pamela R., Wright, David K., Zipkin, Andrew, Pinhasi, Ron, Kennett, Douglas J., Manthi, Fredrick Kyalo, Rohland, Nadin, Patterson, Nick, Reich, David, and Prendergast, Mary E.

Published
2022
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47. Large-scale migration into Britain during the Middle to Late Bronze Age

Author

Patterson, Nick, Isakov, Michael, Booth, Thomas, Büster, Lindsey, Fischer, Claire-Elise, Olalde, Iñigo, Ringbauer, Harald, Akbari, Ali, Cheronet, Olivia, Bleasdale, Madeleine, Adamski, Nicole, Altena, Eveline, Bernardos, Rebecca, Brace, Selina, Broomandkhoshbacht, Nasreen, Callan, Kimberly, Candilio, Francesca, Culleton, Brendan, Curtis, Elizabeth, Demetz, Lea, Carlson, Kellie Sara Duffett, Edwards, Ceiridwen J., Fernandes, Daniel M., Foody, M. George B., Freilich, Suzanne, Goodchild, Helen, Kearns, Aisling, Lawson, Ann Marie, Lazaridis, Iosif, Mah, Matthew, Mallick, Swapan, Mandl, Kirsten, Micco, Adam, Michel, Megan, Morante, Guillermo Bravo, Oppenheimer, Jonas, Özdoğan, Kadir Toykan, Qiu, Lijun, Schattke, Constanze, Stewardson, Kristin, Workman, J. Noah, Zalzala, Fatma, Zhang, Zhao, Agustí, Bibiana, Allen, Tim, Almássy, Katalin, Amkreutz, Luc, Ash, Abigail, Baillif-Ducros, Christèle, Barclay, Alistair, Bartosiewicz, László, Baxter, Katherine, Bernert, Zsolt, Blažek, Jan, Bodružić, Mario, Boissinot, Philippe, Bonsall, Clive, Bradley, Pippa, Brittain, Marcus, Brookes, Alison, Brown, Fraser, Brown, Lisa, Brunning, Richard, Budd, Chelsea, Burmaz, Josip, Canet, Sylvain, Carnicero-Cáceres, Silvia, Čaušević-Bully, Morana, Chamberlain, Andrew, Chauvin, Sébastien, Clough, Sharon, Čondić, Natalija, Coppa, Alfredo, Craig, Oliver, Črešnar, Matija, Cummings, Vicki, Czifra, Szabolcs, Danielisová, Alžběta, Daniels, Robin, Davies, Alex, de Jersey, Philip, Deacon, Jody, Deminger, Csilla, Ditchfield, Peter W., Dizdar, Marko, Dobeš, Miroslav, Dobisíková, Miluše, Domboróczki, László, Drinkall, Gail, Đukić, Ana, Ernée, Michal, Evans, Christopher, Evans, Jane, Fernández-Götz, Manuel, Filipović, Slavica, Fitzpatrick, Andrew, Fokkens, Harry, Fowler, Chris, Fox, Allison, Gallina, Zsolt, Gamble, Michelle, González Morales, Manuel R., González-Rabanal, Borja, Green, Adrian, Gyenesei, Katalin, Habermehl, Diederick, Hajdu, Tamás, Hamilton, Derek, Harris, James, Hayden, Chris, Hendriks, Joep, Hernu, Bénédicte, Hey, Gill, Horňák, Milan, Ilon, Gábor, Istvánovits, Eszter, Jones, Andy M., Kavur, Martina Blečić, Kazek, Kevin, Kenyon, Robert A., Khreisheh, Amal, Kiss, Viktória, Kleijne, Jos, Knight, Mark, Kootker, Lisette M., Kovács, Péter F., Kozubová, Anita, Kulcsár, Gabriella, Kulcsár, Valéria, Le Pennec, Christophe, Legge, Michael, Leivers, Matt, Loe, Louise, López-Costas, Olalla, Lord, Tom, Los, Dženi, Lyall, James, Marín-Arroyo, Ana B., Mason, Philip, Matošević, Damir, Maxted, Andy, McIntyre, Lauren, McKinley, Jacqueline, McSweeney, Kathleen, Meijlink, Bernard, Mende, Balázs G., Menđušić, Marko, Metlička, Milan, Meyer, Sophie, Mihovilić, Kristina, Milasinovic, Lidija, Minnitt, Steve, Moore, Joanna, Morley, Geoff, Mullan, Graham, Musilová, Margaréta, Neil, Benjamin, Nicholls, Rebecca, Novak, Mario, Pala, Maria, Papworth, Martin, Paresys, Cécile, Patten, Ricky, Perkić, Domagoj, Pesti, Krisztina, Petit, Alba, Petriščáková, Katarína, Pichon, Coline, Pickard, Catriona, Pilling, Zoltán, Price, T. Douglas, Radović, Siniša, Redfern, Rebecca, Resutík, Branislav, Rhodes, Daniel T., Richards, Martin B., Roberts, Amy, Roefstra, Jean, Sankot, Pavel, Šefčáková, Alena, Sheridan, Alison, Skae, Sabine, Šmolíková, Miroslava, Somogyi, Krisztina, Somogyvári, Ágnes, Stephens, Mark, Szabó, Géza, Szécsényi-Nagy, Anna, Szeniczey, Tamás, Tabor, Jonathan, Tankó, Károly, Maria, Clenis Tavarez, Terry, Rachel, Teržan, Biba, Teschler-Nicola, Maria, Torres-Martínez, Jesús F., Trapp, Julien, Turle, Ross, Ujvári, Ferenc, van der Heiden, Menno, Veleminsky, Petr, Veselka, Barbara, Vytlačil, Zdeněk, Waddington, Clive, Ware, Paula, Wilkinson, Paul, Wilson, Linda, Wiseman, Rob, Young, Eilidh, Zaninović, Joško, Žitňan, Andrej, Lalueza-Fox, Carles, de Knijff, Peter, Barnes, Ian, Halkon, Peter, Thomas, Mark G., Kennett, Douglas J., Cunliffe, Barry, Lillie, Malcolm, Rohland, Nadin, Pinhasi, Ron, Armit, Ian, and Reich, David

Published
2022
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48. Reconstructing the Deep Population History of Central and South America.

Author

Posth, Cosimo, Nakatsuka, Nathan, Lazaridis, Iosif, Skoglund, Pontus, Mallick, Swapan, Lamnidis, Thiseas C, Rohland, Nadin, Nägele, Kathrin, Adamski, Nicole, Bertolini, Emilie, Broomandkhoshbacht, Nasreen, Cooper, Alan, Culleton, Brendan J, Ferraz, Tiago, Ferry, Matthew, Furtwängler, Anja, Haak, Wolfgang, Harkins, Kelly, Harper, Thomas K, Hünemeier, Tábita, Lawson, Ann Marie, Llamas, Bastien, Michel, Megan, Nelson, Elizabeth, Oppenheimer, Jonas, Patterson, Nick, Schiffels, Stephan, Sedig, Jakob, Stewardson, Kristin, Talamo, Sahra, Wang, Chuan-Chao, Hublin, Jean-Jacques, Hubbe, Mark, Harvati, Katerina, Nuevo Delaunay, Amalia, Beier, Judith, Francken, Michael, Kaulicke, Peter, Reyes-Centeno, Hugo, Rademaker, Kurt, Trask, Willa R, Robinson, Mark, Gutierrez, Said M, Prufer, Keith M, Salazar-García, Domingo C, Chim, Eliane N, Müller Plumm Gomes, Lisiane, Alves, Marcony L, Liryo, Andersen, Inglez, Mariana, Oliveira, Rodrigo E, Bernardo, Danilo V, Barioni, Alberto, Wesolowski, Veronica, Scheifler, Nahuel A, Rivera, Mario A, Plens, Claudia R, Messineo, Pablo G, Figuti, Levy, Corach, Daniel, Scabuzzo, Clara, Eggers, Sabine, DeBlasis, Paulo, Reindel, Markus, Méndez, César, Politis, Gustavo, Tomasto-Cagigao, Elsa, Kennett, Douglas J, Strauss, André, Fehren-Schmitz, Lars, Krause, Johannes, and Reich, David

Subjects
Humans, DNA, Mitochondrial, Genetics, Population, Genome, Human, Models, Theoretical, History, Ancient, Central America, South America, Gene Flow, DNA, Ancient, anthropology, archaeology, population genetics, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

We report genome-wide ancient DNA from 49 individuals forming four parallel time transects in Belize, Brazil, the Central Andes, and the Southern Cone, each dating to at least ∼9,000 years ago. The common ancestral population radiated rapidly from just one of the two early branches that contributed to Native Americans today. We document two previously unappreciated streams of gene flow between North and South America. One affected the Central Andes by ∼4,200 years ago, while the other explains an affinity between the oldest North American genome associated with the Clovis culture and the oldest Central and South Americans from Chile, Brazil, and Belize. However, this was not the primary source for later South Americans, as the other ancient individuals derive from lineages without specific affinity to the Clovis-associated genome, suggesting a population replacement that began at least 9,000 years ago and was followed by substantial population continuity in multiple regions.

Published
2018

49. Current evidence allows multiple models for the peopling of the Americas.

Author

Potter, Ben A, Baichtal, James F, Beaudoin, Alwynne B, Fehren-Schmitz, Lars, Haynes, C Vance, Holliday, Vance T, Holmes, Charles E, Ives, John W, Kelly, Robert L, Llamas, Bastien, Malhi, Ripan S, Miller, D Shane, Reich, David, Reuther, Joshua D, Schiffels, Stephan, and Surovell, Todd A

Subjects
Humans, Population Dynamics, Emigration and Immigration, Models, Theoretical, History, Ancient, Americas, Biological Evolution, Models, Theoretical, History, Ancient
Abstract

Some recent academic and popular literature implies that the problem of the colonization of the Americas has been largely resolved in favor of one specific model: a Pacific coastal migration, dependent on high marine productivity, from the Bering Strait to South America, thousands of years before Clovis, the earliest widespread cultural manifestation south of the glacial ice. Speculations on maritime adaptations and typological links (stemmed points) across thousands of kilometers have also been advanced. A review of the current genetic, archeological, and paleoecological evidence indicates that ancestral Native American population expansion occurred after 16,000 years ago, consistent with the archeological record, particularly with the earliest securely dated sites after ~15,000 years ago. These data are largely consistent with either an inland (ice-free corridor) or Pacific coastal routes (or both), but neither can be rejected at present. Systematic archeological and paleoecological investigations, informed by geomorphology, are required to test each hypothesis.

Published
2018

50. Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Author

Jun, Goo, Manning, Alisa, Almeida, Marcio, Zawistowski, Matthew, Wood, Andrew R, Teslovich, Tanya M, Fuchsberger, Christian, Feng, Shuang, Cingolani, Pablo, Gaulton, Kyle J, Dyer, Thomas, Blackwell, Thomas W, Chen, Han, Chines, Peter S, Choi, Sungkyoung, Churchhouse, Claire, Fontanillas, Pierre, King, Ryan, Lee, SungYoung, Lincoln, Stephen E, Trubetskoy, Vasily, DePristo, Mark, Fingerlin, Tasha, Grossman, Robert, Grundstad, Jason, Heath, Alison, Kim, Jayoun, Kim, Young Jin, Laramie, Jason, Lee, Jaehoon, Li, Heng, Liu, Xuanyao, Livne, Oren, Locke, Adam E, Maller, Julian, Mazur, Alexander, Morris, Andrew P, Pollin, Toni I, Ragona, Derek, Reich, David, Rivas, Manuel A, Scott, Laura J, Sim, Xueling, Tearle, Rick G, Teo, Yik Ying, Williams, Amy L, Zöllner, Sebastian, Curran, Joanne E, Peralta, Juan, Akolkar, Beena, Bell, Graeme I, Burtt, Noël P, Cox, Nancy J, Florez, Jose C, Hanis, Craig L, McKeon, Catherine, Mohlke, Karen L, Seielstad, Mark, Wilson, James G, Atzmon, Gil, Below, Jennifer E, Dupuis, Josée, Nicolae, Dan L, Lehman, Donna, Park, Taesung, Won, Sungho, Sladek, Robert, Altshuler, David, McCarthy, Mark I, Duggirala, Ravindranath, Boehnke, Michael, Frayling, Timothy M, Abecasis, Gonçalo R, and Blangero, John

Subjects
Diabetes, Genetics, Human Genome, Clinical Research, Obesity, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Family Health, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Male, Mexican Americans, Pedigree, Phenotype, Quantitative Trait Loci, Whole Genome Sequencing, genetics, sequencing, type 2 diabetes, eQTL, rare variants
Abstract

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Published
2018

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