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BackgroundCOVID-19 has been associated with an increased risk of incident dementia (post-COVID dementia). Establishing additional risk markers may help identify at-risk individuals and guide clinical decision-making.MethodsWe investigated pre-COVID psychotropic medication use (exposure) and 1-year incidence of dementia (outcome) in 1,755 patients (≥65 years) hospitalized with COVID-19. Logistic regression models were used to examine the association, adjusting for demographic and clinical variables. For further confirmation, we applied the Least Absolute Shrinkage and Selection Operator (LASSO) regression and a machine learning (Random Forest) algorithm.ResultsOne-year incidence rate of post-COVID dementia was 12.7% (N = 223). Pre-COVID psychotropic medications (OR = 2.7, 95% CI: 1.8–4.0, P < 0.001) and delirium (OR = 3.0, 95% CI: 1.9–4.6, P < 0.001) were significantly associated with greater 1-year incidence of post-COVID dementia. The association between psychotropic medications and incident dementia remained robust when the analysis was restricted to the 423 patients with at least one documented neurological or psychiatric diagnosis at the time of COVID-19 admission (OR = 3.09, 95% CI: 1.5–6.6, P = 0.002). Across different drug classes, antipsychotics (OR = 2.8, 95% CI: 1.7–4.4, P < 0.001) and mood stabilizers/anticonvulsants (OR = 2.4, 95% CI: 1.39–4.02, P = 0.001) displayed the greatest association with post-COVID dementia. The association of psychotropic medication with dementia was further confirmed with Random Forest and LASSO analysis.ConclusionConfirming prior studies we observed a high dementia incidence in older patients after COVID-19 hospitalization. Pre-COVID psychotropic medications were associated with higher risk of incident dementia. Psychotropic medications may be risk markers that signify neuropsychiatric symptoms during prodromal dementia, and not mutually exclusive, contribute to post-COVID dementia.

A standard pathway/gene-set enrichment analysis, the over-representation analysis, is based on four values: the size of two gene-sets, size of their overlap, and size of the gene universe from which the gene-sets are chosen. The standard result of such an analysis is based on the p-value of a statistical test. We supplement this standard pipeline by six cautions: (1) any p-value threshold to distinguish enriched gene-sets from not-enriched ones is to certain degree arbitrary; (2) genes in a gene-set may be correlated, which potentially overcount the gene-set size; (3) any attempt to impose multiple testing correction will increase the false negative rate; (4) gene-sets in a gene-set database may be correlated, potentially overcount the factor for multiple testing correction; (5) the discrete nature of the data make it possible that a minimum change in counts may lead to a quantum change in the p-value threshold-based conclusion; (6) the two gene-sets may not be chosen from the universe of all human genes, but in fact from a subset of that universe, or even two different subsets of all genes. Careful reconsideration of these issues can have an impact on an enrichment analysis conclusion. Part of our cautions mirror the call from statistician that reaching conclusion from data is not a simple matter of p-value smaller than 0.05, but a thoughtful process with due diligences.

Objectives Older adults are particularly vulnerable to the negative consequences of antipsychotic exposure and are disproportionally affected by higher mortality from coronavirus disease 2019 (COVID-19). Our goal was to determine whether concurrent antipsychotic medication use was associated with increased COVID-19 mortality in older patients with preexisting behavioral health problems. We also report on findings from post-COVID follow-ups. Design Retrospective observational study. Participants Outpatients at a geriatric psychiatric clinic in New York City. Measurements Demographic and clinical data including medication, diagnosis and Clinical Global Impression Severity (CGI-S) scales on outpatients who had COVID-19 between February 28th and October 1st 2020 were extracted from the electronic health records (EHR) from the hospital. Results A total of 56 patients were diagnosed with COVID-19 (mean age 76 years; median age 75 years) and 13 (23.2%) died. We found an increased mortality risk for patients who were prescribed at least one antipsychotic medication at the time of COVID-19 infection (Fisher’s exact test P = 0.009, OR = 11.1, 95% confidence interval: 1.4–96.0). This result remains significant after adjusting for age, gender, housing context and dementia (Logistic regression P = 0.035, Beta = 2.4). Furthermore, we found that most patients who survived COVID-19 (88.4%) recovered to pre-COVID baseline in terms of psychiatric symptoms. Comparison of pre- and post-COVID assessments of CGI-S for 33 patients who recovered from COVID-19 were not significantly different. Conclusion We observed a higher COVID-19 mortality associated with concurrent antipsychotics use in older patients receiving behavioral health services. The majority of patients in our geriatric clinic who recovered from COVID-19 appeared to return to their pre-COVID psychiatric function. More precise estimates of the risk associated with antipsychotic treatment in older patients with COVID-19 and other underlying factors will come from larger datasets and meta-analyses.

To evaluate how age and apolipoprotein E-e4 (APOE4) status interact with APOE-independent polygenic risk score (PRSnon-APOE), we estimated PRSnon-APOE in superagers (age ≥ 90 years, N = 346), 89− controls (age 60–89, N = 2930), and Alzheimer's disease (AD) cases (N = 1760). Using superagers, we see a nearly 5 times greater odds ratio (OR) for AD comparing the top PRSnon-APOE decile to the lowest decile (OR = 4.82, p = 2.5 × 10−6), which is twice the OR as using 89− controls (OR = 2.38, p = 4.6 × 10−9). Thus PRSnon-APOE is correlated with age, which in turn is associated with APOE. Further exploring these relationships, we find that PRSnon-APOE modifies age at onset among APOE4 carriers, but not among noncarriers. More specifically, PRSnon-APOE in the top decile predicts an age at onset 5 years earlier compared with the lowest decile (70.1 vs. 75.0 years; t-test p = 2.4 × 10−5) among APOE4 carriers. This disproportionally large PRSnon-APOE among younger APOE4-positive cases is reflected in a significant statistical interaction between APOE4 status and age at onset (β = −0.02, p = 4.8 × 10−3) as a predictor of PRSnon-APOE. Thus, the known AD risk variants are particularly detrimental in young APOE4 carriers.

Introduction The novel coronavirus disease 2019 (COVID-19) disproportionally affects elderly patients leading to particularly high morbidity and mortality rates in this population. Age, gender, comorbidities, and housing context have been reported to be among the risk factors for mortality. Exposure to antipsychotics have been discussed to potentially impact the immune response and may pose additional risks. Furthermore, neuropsychiatric presentations are common among older patients and it is unclear how geriatric patients with preexisting psychiatric and neuropsychiatric problems recover from COVID-19. Methods In this retrospective observational study, we describe demographic characteristics of patients at a large geriatric psychiatric outpatient clinic in the New York metropolitan area, who had COVID-19. Our aim is to identify factors that may be associated with increased mortality and to evaluate whether those who survived returned to pre-COVID baseline function. We combined information provided by the treating psychiatrists with data that could be extracted from the electronic health records. Results Between February and September 2020, we identified 56 patients who were diagnosed with COVID-19 (mean age 76 years old). Thirteen patients (23.2%) died and we found that antipsychotics use at the time of COVID-19 infection is associated with increased risk of death (Fisher's exact test P= 0.009, odds ratio = 11.5, 95% confidence interval: 1.4 – 96.0). The result remains significant after adjusting for age, gender, housing context and presence of neurocognitive disorder (Logistic regression P=0.037, Beta=2.4). Furthermore, we found that most patients who survived COVID-19 recovered to baseline (88.4%) as indicated by the ratio of pre- and post-COVID Clinical Global Impressions Severity scale (mean ratio= 0.98, median=1.0, One-sample t-test P=0.48) in 33 patients. Conclusions In conclusion, antipsychotics appear to be associated with higher mortality in our geriatric psychiatry outpatient cohort. However, it is encouraging to find that the majority of elderly patients who survived COVID-19 seems to recover to their baseline neuropsychiatric function. Future larger studies are needed to put these observations into a broader context as well as to explore underlying mechanisms of risk factors. Funding NIH K08 AG054727

The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

The purpose of this study was to examine the potential effect modifying role of the BDNF Val66Met polymorphism on the association of soccer heading with white matter microstructure. We studied 312 players enrolled in the ongoing Einstein Soccer Study, a longitudinal study of amateur soccer player in New York City and surrounding areas. At enrollment and 2 years later, total heading in the prior 12 months (12-mo.) was estimated using an established self-report instrument and diffusion tensor imaging (DTI) was performed. Generalized Estimating Equations (GEE) logistic regression models were employed to test effect modification by the BDNF Val66Met polymorphism on the association between 12-mo. heading exposure and DTI. We identified a significant interaction of 12-mo heading*BDNF Val66Met genotype on the presence of low Radial Diffusivity, a DTI marker associated with myelination. Only Met (+) players demonstrated significantly reduced odds of low RD [OR (95 % CI): −2.36 (−3.53, −1.19)] associated with the highest vs. lowest quartile of 12-mo heading exposure. BDNF Val66Met (+) soccer players with long-term exposure to high levels of heading exhibit less low Radial Diffusivity, suggesting impaired re-myelination may be a substrate of the previously reported association between heading and poor functional outcomes in soccer players.

The nonadherence rate to psychiatric medications among the geriatric patient population is estimated to be similar to that in the younger adult population, around 50%. Contributing factors to psychotropic medication nonadherence include patient-specific risk factors (for example, illness beliefs and cognitive function), drug-specific factors (for example, adverse effects and cost), as well as social factors (e.g., family support). Randomized controlled trials on geriatric adherence to psychiatric medications are scarce. We propose strategies that are better adapted to the geriatric population to improve medication adherence.

We compared coding region variants of 53 cognitively healthy centenarians and 45 patients with Alzheimer’s disease (AD), all of Ashkenazi Jewish (AJ) ancestry. Despite the small sample size, the known AD risk variant APOE4 reached genome-wide significance, indicating the advantage of utilizing ‘super-controls’. We restricted our subsequent analysis to rare variants observed at most once in the 1000 Genomes database and having a minor allele frequency below 2% in our AJ sample. We compared the burden of predicted protein altering variants between cases and controls as normalized by the level of rare synonymous variants. We observed an increased burden among AD subjects for predicted loss-of-function (LoFs) variants defined as stop-gain, frame shift, initiation codon (INIT) and splice site mutations (n = 930, OR = 1.3, P = 1.5×E−5). There was no enrichment across all rare protein altering variants defined as missense plus LoFs, in frame indels and stop-loss variants (n = 13 014, OR = 0.97, P = 0.47). Among LoFs, the strongest burden was observed for INIT (OR = 2.16, P = 0.0097) and premature stop variants predicted to cause non-sense-mediated decay in the majority of transcripts (NMD) (OR = 1.98, P = 0.02). Notably, this increased burden of NMD, INIT and splice variants was more pronounced in a set of 1397 innate immune genes (OR = 4.55, P = 0.0043). Further comparison to additional exomes indicates that the difference in LoF burden originated both from the AD and centenarian sample. In summary, we observed an overall increased burden of rare LoFs in AD subjects as compared to centenarians, and this enrichment is more pronounced for innate immune genes.