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The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City 1 . Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent. Genotype and exome sequencing of 150,000 participants and whole-genome sequencing of 9,950 selected individuals recruited into the Mexico City Prospective Study constitute a valuable, publicly available resource of non-European sequencing data.

Background Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored. Methods To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers. Results We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer. Conclusions Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

[...]exome sequencing-which is focused on the protein-coding regions of the genome-may directly implicate genes in phenotype variability through burden testing of multiple rare protein-coding variants15. [...]analysis of rare coding variation can help establish the directionality of impaired gene function through the analysis of loss-of-function (LOF) alleles, a feature that can be informative both for understanding disease mechanisms and for potential therapeutic targeting. [...]we describe the frequency of mutations in genes underlying cardiovascular diseases and monogenic diabetes. Importantly, the novel associations that we identified remained robust in a LOVO analysis (Supplementary Fig. 10). [...]the genes significantly associated with diseases or traits were identified due to a burden of multiple contributing rare variants, although in certain cases-such as the associations of ANGPTL2 with height and NR1H3 with HDL-single variants were important.

To better understand the genetics of hearing loss, we performed a genome-wide association meta-analysis with 125,749 cases and 469,497 controls across five cohorts. We identified 53/c loci affecting hearing loss risk, including common coding variants in COL9A3 and TMPRSS3 . Through exome sequencing of 108,415 cases and 329,581 controls, we observed rare coding associations with 11 Mendelian hearing loss genes, including additive effects in known hearing loss genes GJB2 (Gly12fs; odds ratio [OR] = 1.21, P  = 4.2 × 10 −11 ) and SLC26A5 (gene burden; OR = 1.96, P  = 2.8 × 10 −17 ). We also identified hearing loss associations with rare coding variants in FSCN2 (OR = 1.14, P  = 1.9 × 10 −15 ) and KLHDC7B (OR = 2.14, P  = 5.2 × 10 −30 ). Our results suggest a shared etiology between Mendelian and common hearing loss in adults. This work illustrates the potential of large-scale exome sequencing to elucidate the genetic architecture of common disorders where both common and rare variation contribute to risk. A GWAS and exome-wide association study meta-analysis identifies 53 loci affecting hearing loss risk from over half a million individuals across five cohorts. Rare variants in Mendelian hearing loss genes contribute to hearing loss risk in adults.

The Mexico City Prospective Study (MCPS) is a prospective cohort of over 150,000 adults recruited two decades ago from the urban districts of Coyoacan and Iztapalapa in Mexico City. We generated genotype and exome sequencing data for all individuals, and whole genome sequencing for 10,000 selected individuals. We uncovered high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Native American, European and African ancestry, with extensive admixture from indigenous groups in Central, Southern and South Eastern Mexico. Native Mexican segments of the genome had lower levels of coding variation, but an excess of homozygous loss of function variants compared with segments of African and European origin. We estimated population specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Native Mexico at exome variants, all available via a public browser. Using whole genome sequencing, we developed an imputation reference panel which outperforms existing panels at common variants in individuals with high proportions of Central, South and South Eastern Native Mexican ancestry. Our work illustrates the value of genetic studies in populations with diverse ancestry and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States where the Hispanic/Latino population is predominantly of Mexican descent. Competing Interest Statement Andrey Ziyatdinov, Joshua Backman, Joelle Mbatchou, Sheila M. Gaynor, Tyler Joseph, Yuxin Zou, Daren Liu, Jeffrey Staples, Razvan Panea, Xiaodong Bai, Suganthi Balasubramanian, Lukas Habegger, Rouel Lanche, Alex Lopez, Evan Maxwell, Marcus Jones, Eric Jorgenson, William Salerno, John Overton, Jeffrey Reid, Timothy Thornton, Goncalo Abecasis, Aris Baras, Jonathan Marchini are current employees and/or stockholders of Regeneron Genetics Center or Regeneron Pharmaceuticals. Abhishek Nag, Katherine Smith and Slave Petrovski are current employees and/or stockholders of AstraZeneca Mark Reppell is current employee and/or stockholder of AbbVie.