Search

PurposeAlpelisib is a PI3K alpha (PI3Kα)-selective inhibitor approved for the treatment of hormone receptor-positive/HER2-negative (HR+/HER2-) PIK3CA-mutated advanced breast cancer (ABC) based on the SOLAR-1 trial, which defined 11 substitutions in exons 7, 9, and 20 in PIK3CA (SOLAR1m). We report alpelisib effectiveness for ABC harboring SOLAR1m, as well as other pathogenic PIK3CA mutations (OTHERm) using comprehensive genomic profiling (CGP).Experimental designA total of 33,977 tissue and 1,587 liquid biopsies were analyzed using hybrid capture-based CGP covering the entire coding sequence of PIK3CA. Clinical characteristics and treatment history were available for 10,750 patients with ABC in the deidentified Flatiron Health-Foundation Medicine clinico-genomic database (FH-FMI CGDB).ResultsPIK3CAm were detected in 11,767/33,977 (35%) of tissue biopsies, including 2,300 (7%) samples with OTHERm and no SOLAR1m. Liquid biopsy had 77% sensitivity detecting PIK3CAm, increasing to 95% with circulating tumor DNA fraction ≥2%. In patients with HR+/HER2- ABC and PIK3CAm receiving alpelisib/fulvestrant (ALP+FUL; n = 182) or fulvestrant alone (FUL; n = 119), median real-world progression-free survival (rwPFS) was 5.9 months on ALP+FUL [95% confidence interval (CI): 5.1-7.4] versus 3.1 months on FUL (95% CI: 2.7-3.7; P < 0.0001). In patients with OTHERm, median rwPFS was 4.0 months on ALP+FUL (95% CI: 2.8-10.1) versus 2.5 months on FUL (95% CI: 2.2-3.7; P = 0.0054).ConclusionsCGP detects diverse PIK3CAm in a greater number of patients with ABC than PCR hotspot testing; 20% of patients with PIK3CAm do not have SOLAR1m. These patients may derive benefit from alpelisib. See related commentary by Tau and Miller, p. 989.

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P

BackgroundNeurotrophic tyrosine receptor kinase (NTRK) gene fusions are oncogenic drivers in various tumor types. While NTRK gene fusions are predictive of benefit from tropomyosin receptor kinase inhibitors regardless of tumor type, the prognostic significance of NTRK gene fusions in a pan-tumor setting remains unclear.ObjectiveThis study evaluated the characteristics and prognosis of tropomyosin receptor kinase fusion cancer in the real-world setting.Patients and methodsThis retrospective study used a de-identified clinico-genomic database and included patients with cancer who had comprehensive genomic profiling between January 2011 and July 2018. Patients were classified as having cancer with NTRK gene fusions or NTRK wild-type genes. Patients were matched with a 1:4 ratio (NTRK fusion:NTRK wild-type) using the Mahalanobis distance method on demographic and clinical characteristics, including age and Eastern Cooperative Oncology Group performance status. Descriptive analysis of clinical and molecular characteristics was conducted. Kaplan-Meier estimator and Cox regression were used for overall survival analysis.ResultsMedian overall survival was 12.5 months (95% confidence interval 9.5-not estimable) and 16.5 months (95% confidence interval 12.5-22.5) in the NTRK gene fusion (n = 27) and NTRK wild-type cohorts (n = 107), respectively (hazard ratio 1.44; 95% confidence interval 0.61-3.37; p = 0.648). Co-occurrence of select targetable biomarkers including ALK, BRAF, ERBB2, EGFR, ROS1, and KRAS was lower in cancers with NTRK gene fusions than in NTRK wild-type cancers.ConclusionsAlthough the hazard ratio for overall survival suggested a higher risk of death for patients with NTRK gene fusions, the difference was not statistically significant. Co-occurrence of NTRK gene fusions and other actionable biomarkers was uncommon.

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10-8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.

The clinically standardised mindfulness‐based stress reduction (MBSR) has been utilised as an intervention for improving mental health among diabetes patients The present study aimed to assess the effectiveness of mindfulness‐based stress reduction (MBSR) on the mental health, haemoglobin A1c (HbA1C), and mindfulness of diabetes patients. A systematic review and meta‐analysis approach was employed to review randomised controlled trials published in the English language between the inception of eight databases to July 2022. Eleven articles from 10 studies, with a combined sample size of 718 participants, were included in the systematic review, and nine studies were included in the meta‐analysis. In the meta‐analysis, outcomes at post‐intervention and follow‐up were compared between the MBSR intervention and control groups with an adjustment of the baseline values. The results showed that MBSR demonstrated effects at post‐intervention and follow‐up (in a period between one to 12 months with a mean length of 4.3 months) in reducing anxiety and depressive symptoms, and enhancing mindfulness, with large effect sizes. However, the effect of MBSR on reducing stress was observed at follow‐up, but not at post‐intervention. Effects of MBSR on HbA1C were not detected at post‐intervention and follow‐up. The findings suggest that MBSR appears to be an effective treatment for improving mental health conditions and mindfulness in people with diabetes. The measurement of cortisol is recommended to be used as a biological measure to evaluate the effectiveness of MBSR in diabetes patients in future research. [ABSTRACT FROM AUTHOR]