Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults.

Reducing premature mortality associated with age-related chronic diseases, such as cancer and cardiovascular disease, is an urgent priority. We report early results using genomics in combination with advanced imaging and other clinical testing to proactively screen for age-related chronic disease risk among adults. We enrolled active, symptom-free adults in a study of screening for age-related chronic diseases associated with premature mortality. In addition to personal and family medical history and other clinical testing, we obtained whole-genome sequencing (WGS), noncontrast whole-body MRI, dual-energy X-ray absorptiometry (DXA), global metabolomics, a new blood test for prediabetes (Quantose IR), echocardiography (ECHO), ECG, and cardiac rhythm monitoring to identify age-related chronic disease risks. Precision medicine screening using WGS and advanced imaging along with other testing among active, symptom-free adults identified a broad set of complementary age-related chronic disease risks associated with premature mortality and strengthened WGS variant interpretation. This and other similarly designed screening approaches anchored by WGS and advanced imaging may have the potential to extend healthy life among active adults through improved prevention and early detection of age-related chronic diseases (and their risk factors) associated with premature mortality.

Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes.

Short tandem repeats (STRs) are hyper-mutable sequences in the human genome. They are often used in forensics and population genetics and are also the underlying cause of many genetic diseases. There are challenges associated with accurately determining the length polymorphism of STR loci in the genome by next-generation sequencing (NGS). In particular, accurate detection of pathological STR expansion is limited by the sequence read length during whole-genome analysis. We developed TREDPARSE, a software package that incorporates various cues from read alignment and paired-end distance distribution, as well as a sequence stutter model, in a probabilistic framework to infer repeat sizes for genetic loci, and we used this software to infer repeat sizes for 30 known disease loci. Using simulated data, we show that TREDPARSE outperforms other available software. We sampled the full genome sequences of 12,632 individuals to an average read depth of approximately 30× to 40× with Illumina HiSeq X. We identified 138 individuals with risk alleles at 15 STR disease loci. We validated a representative subset of the samples (n = 19) by Sanger and by Oxford Nanopore sequencing. Additionally, we validated the STR calls against known allele sizes in a set of GeT-RM reference cell-line materials (n = 6). Several STR loci that are entirely guanine or cytosines (G or C) have insufficient read evidence for inference and therefore could not be assayed precisely by TREDPARSE. TREDPARSE extends the limit of STR size detection beyond the physical sequence read length. This extension is critical because many of the disease risk cutoffs are close to or beyond the short sequence read length of 100 to 150 bases.

Identification of individuals by trait prediction using whole-genome sequencing data.

Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.

The human noncoding genome defined by genetic diversity.

Understanding the significance of genetic variants in the noncoding genome is emerging as the next challenge in human genomics. We used the power of 11,257 whole-genome sequences and 16,384 heptamers (7-nt motifs) to build a map of sequence constraint for the human species. This build differed substantially from traditional maps of interspecies conservation and identified regulatory elements among the most constrained regions of the genome. Using new Hi-C experimental data, we describe a strong pattern of coordination over 2 Mb where the most constrained regulatory elements associate with the most essential genes. Constrained regions of the noncoding genome are up to 52-fold enriched for known pathogenic variants as compared to unconstrained regions (21-fold when compared to the genome average). This map of sequence constraint across thousands of individuals is an asset to help interpret noncoding elements in the human genome, prioritize variants and reconsider gene units at a larger scale.