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Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E−10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes.

Background Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test. Methods A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K ( n  = 76) or EPIC 850K ( n  = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05. Results At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2 , and APBB1IP . Conclusions Using prospective time-to-event data, we detected associations between CADM1 -, DAPK1 -, PAX1 -, and RARB -related CpGs and cervical disease progression, and we identified novel progression-associated CpGs. Impact Methylation levels at novel CpG sites may help identify individuals with ≤CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines.

Background: Faster rates of cognitive decline are likely to result in earlier onset of cognitive impairment and dementia. d-galactose, a derivative of lactose, is used in animal studies to induce neurodegeneration. Milk is the primary source of lactose in the human diet, and its effects on cognitive decline have not been fully evaluated. Objective: Assess the association of milk intake with change in cognitive function over 20 years. Methods: A total of 13,751 participants of the Atherosclerosis Risk in Communities (ARIC) cohort completed a food frequency questionnaire and three neurocognitive evaluations from 1990 through 2013. Two single nucleotide polymorphisms (SNPs) were used to determine lactase persistence (LCT-13910 C/T for Whites and LCT-14010 G/C for Blacks). Mixed-effects models were used to study the association of milk intake with cognitive change. Multiple imputations by chained equations were used to account for attrition. Results: Milk intake greater than 1 glass/day was associated with greater decline in the global z-score over a 20-year period. The difference in decline was 0.10 (95% CI: 0.16, 0.03) z-scores, or an additional 10% decline, relative to the group reporting “almost never” consuming milk. Conclusions: Replication of these results is warranted in diverse populations with greater milk intake and higher variability of lactase persistence genotype.

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic Bio Me biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1 , with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease. Diseases often run in families. These disease are frequently linked to changes in DNA that are passed down through generations. Close family members may share these disease-causing mutations; so may distant relatives who inherited the same mutation from a common ancestor long ago. Geneticists use a method called linkage mapping to trace a disease found in multiple members of a family over generations to genetic changes in a shared ancestor. This allows scientists to pinpoint the exact place in the genome the disease-causing mutation occurred. Using computer algorithms, scientists can apply the same technique to identify mutations that distant relatives inherited from a common ancestor. Belbin et al. used this computational technique to identify a mutation that may cause unusually short stature or bone and joint problems in up to 2% of people of Puerto Rican descent. In the experiments, the genomes of about 32,000 New Yorkers who have volunteered to participate in the BioMe Biobank and their health records were used to search for genetic changes linked to extremely short stature. The search revealed that people who inherited two copies of this mutation from their parents were likely to be extremely short or to have bone and joint problems. People who inherited one copy had an increased likelihood of joint or bone problems. This mutation affects a gene responsible for making a form of protein called collagen that is important for bone growth. The analysis suggests the mutation first arose in a Native American ancestor living in Puerto Rico around the time that European colonization began. The mutation had previously been linked to a disorder called Steel syndrome that was thought to be rare. Belbin et al. showed this condition is actually fairly common in people whose ancestors recently came from Puerto Rico, but may often go undiagnosed by their physicians. The experiments emphasize the importance of including diverse populations in genetic studies, as studies of people of predominantly European descent would likely have missed the link between this disease and mutation.

ObjectivesInfant anthropometric growth varies across socioeconomic factors, including maternal education and income, and may serve as an indicator of environmental influences in early life with long-term health consequences. Previous research has identified sociodemographic gradients in growth with a focus on the first year and beyond, but estimates are sparse for growth before 6 months. Thus, our objective was to examine the relationship between sociodemographic factors and infant growth patterns between birth and 5 months of age.DesignProspective cohort study.SettingsLow-income to middle-income neighbourhoods in Santiago, Chile (1991–1996).Participants1412 participants from a randomised iron-deficiency anaemia preventive trial in healthy infants.Main outcome measuresLongitudinal anthropometrics including monthly weight (kg), length (cm) and weight-for-length (WFL) values. For each measure, we estimated three individual-level growth parameters (size, timing and velocity) from SuperImposition by Translation and Rotation models. Size and timing changes represent vertical and horizontal growth curve shifts, respectively, and velocity change represents growth rate shifts. We estimated the linear association between growth parameters and gestational age, maternal age, education and socioeconomic position (SEP).ResultsLower SEP was associated with a slower linear (length) velocity growth parameter (−0.22, 95% CI –0.31 to –0.13)—outcome units are per cent change in velocity from the average growth curve. Lower SEP was associated with later WFL growth timing as demonstrated through the tempo growth parameter for females (0.25, 95% CI 0.05 to 0.42)—outcome units are shifts in days from the average growth curve. We found no evidence of associations between SEP and the weight size, timing or velocity growth rate parameters.ConclusionPrevious research on growth in older infants and children shows associations between lower SEP with slower length velocity. We found evidence supporting this association in the first 5 months of life, which may inform age-specific prevention efforts aimed at infant length growth.

Even though there has been great success in identifying lipid-associated single-nucleotide polymorphisms (SNPs), the mechanisms through which the SNPs act on each trait are poorly understood. The emergence of large, complex biological data sets in well-characterized cohort studies offers an opportunity to investigate the genetic effects on trait variability as a way of informing the causal genes and biochemical pathways that are involved in lipoprotein metabolism. However, methods for simultaneously analyzing multiple omics, environmental exposures, and longitudinally measured, correlated phenotypes are lacking. The purpose of our study was to demonstrate the utility of the structural equation modeling (SEM) approach to inform our understanding of the pathways by which genetic variants lead to disease risk. With the SEM method, we examine multiple pathways directly and indirectly through previously identified triglyceride (TG)-associated SNPs, methylation, and high-density lipoprotein (HDL), including sex, age, and smoking behavior, while adding in biologically plausible direct and indirect pathways. We observed significant SNP effects ( P  < 0.05 and directionally consistent) on TGs at visit 4 (TG4) for five loci, including rs645040 ( DOCK7 ), rs964184 ( ZPR1 / ZNF259 ), rs4765127 ( ZNF664 ), rs1121980 ( FTO ), and rs10401969 ( SUGP1 ). Across these loci, we identify three with strong evidence of an indirect genetic effect on TG4 through HDL, one with evidence of pleiotropic effect on HDL and TG4, and one variant that acts on TG4 indirectly through a nearby methylation site. Such information can be used to prioritize candidate genes in regions of interest, inform mechanisms of action of methylation effects, and highlight possible genes with pleiotropic effects.

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n  = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease ( HLA-DQA1 p  = 4 × 10 −17 ), arthritis ( GDF5 p  = 4 × 10 −13 ), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing. Muscle weakness has been associated with morbidity and mortality in older people. Here, the authors have investigated this trait further by performing a genome-wide meta-analysis of grip strength and Mendelian randomization to discover causal relationships between muscle weakness and other diseases.

Background Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test. Methods A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K (n = 76) or EPIC 850K (n = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05. Results At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2, and APBB1IP. Conclusions Using prospective time-to-event data, we detected associations between CADM1-, DAPK1-, PAX1-, and RARB-related CpGs and cervical disease progression, and we identified novel progression-associated CpGs. Impact Methylation levels at novel CpG sites may help identify individuals with [less than or equal to]CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines. Keywords: Cervical cancer, Cancer surveillance and screening, DNA methylation, Epigenomics, Epigenetics, Cancer risk, Pre-neoplasia

Objective:Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population.Subjects:Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models.Results:We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10- 7 ). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue.Conclusion:Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

Abstract Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4 . LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.