Sihao Xiao

Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity and mortality. Here we developed a proteomic age clock in the UK Biobank (n = 45,441) using a proteomic platform comprising 2,897 plasma proteins and explored its utility to predict major disease morbidity and mortality in diverse populations. We identified 204 proteins that accurately predict chronological age (Pearson r = 0.94) and found that proteomic aging was associated with the incidence of 18 major chronic diseases (including diseases of the heart, liver, kidney and lung, diabetes, neurodegeneration and cancer), as well as with multimorbidity and all-cause mortality risk. Proteomic aging was also associated with age-related measures of biological, physical and cognitive function, including telomere length, frailty index and reaction time. Proteins contributing most substantially to the proteomic age clock are involved in numerous biological functions, including extracellular matrix interactions, immune response and inflammation, hormone regulation and reproduction, neuronal structure and function and development and differentiation. In a validation study involving biobanks in China (n = 3,977) and Finland (n = 1,990), the proteomic age clock showed similar age prediction accuracy (Pearson r = 0.92 and r = 0.94, respectively) compared to its performance in the UK Biobank. Our results demonstrate that proteomic aging involves proteins spanning multiple functional categories and can be used to predict age-related functional status, multimorbidity and mortality risk across geographically and genetically diverse populations.

Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant multisystemic vascular dysplasia, characterized by arteriovenous malformations (AVMs), mucocutaneous telangiectasia and nosebleeds. HHT is caused by a heterozygous null allele in ACVRL1, ENG, or SMAD4, which encode proteins mediating bone morphogenetic protein (BMP) signaling. Several missense and stop-gain variants identified in GDF2 (encoding BMP9) have been reported to cause a vascular anomaly syndrome similar to HHT, however none of these patients met diagnostic criteria for HHT. HHT families from UK NHS Genomic Medicine Centres were recruited to the Genomics England 100,000 Genomes Project. Whole genome sequencing and tiering protocols identified a novel, heterozygous GDF2 sequence variant in all three affected members of one HHT family who had previously screened negative for ACVRL1, ENG, and SMAD4. All three had nosebleeds and typical HHT telangiectasia, and the proband also had severe pulmonary AVMs from childhood. In vitro studies showed the mutant construct expressed the proprotein but lacked active mature BMP9 dimer, suggesting the mutation disrupts correct cleavage of the protein. Plasma BMP9 levels in the patients were significantly lower than controls. In conclusion, we propose that this heterozygous GDF2 variant is a rare cause of HHT associated with pulmonary AVMs.

Turbulent fecal and tissue microbiome dysbiosis of colorectal carcinoma and adenoma has been identified, and some taxa have been proven to be carcinogenic. However, the microbiomes of surrounding adjacent tissues of colonic cancerous tissues were seldom investigated uniformly on a large scale. Here, we characterize the microbiome signatures and dysbiosis of various colonic cancer sample groups. We found a high correlation between colorectal carcinoma adjacent tissue microbiomes and their on-site counterparts. We also discovered that the microbiome dysbiosis in adjacent tissues could discriminate colorectal carcinomas from healthy controls effectively. These results extend our knowledge on the microbial profile of colorectal cancer tissues and highlight microbiota dysbiosis in the surrounding tissues. They also suggest that microbial feature variations of cancerous lesion-adjacent tissues might help to reveal the microbial etiology of colonic cancer and could ultimately be applied for diagnostic and screening purposes.

Abstract Circulating plasma proteins play key roles in human health and could be used to measure biological aging to predict risk of mortality, disease, and multimorbidity beyond chronological age. We developed a proteomic age clock using 1,459 plasma proteins (Olink Explore) in two prospective biobanks in the UK (n=45,117) and China (n=2,026) and explored its utility to predict incident risk of 26 major age-related diseases and all-cause mortality. We identified 226 proteins that accurately predicted chronological age (Pearson r=0.92). Individuals in the top versus bottom deciles of accelerated proteomic aging differed by approximately 10 years of biological aging. In the UK population, accelerated proteomic aging was associated with 25 aging phenotypes (e.g., telomere length, IGF-1, creatinine, cystatin C, hand grip strength, cognitive function, frailty index), 18 chronic diseases (e.g., diseases of the heart, liver, kidneys, lungs; diabetes; neurodegeneration; cancers), multimorbidity, and all-cause mortality. In the smaller Chinese population, accelerated proteomic aging was associated with ischemic heart disease, stroke, and all-cause mortality. Our results demonstrate that plasma proteins are a reliable instrument for prediction of multiple common diseases in diverse populations and can be used as a robust biochemical aging signature to improve early detection and management of common diseases.

For rare inherited diseases an important question is what type of clinical diagnostic test to select, for instance Sanger-based single genesequencing; a high read depth gene panel; whole exomesequencingor whole genome sequencing. There is emerging recognitionthat a transmissible parental variant present at less than expected heterozygous frequency (due to mosaicism) may escape detection by certain methods. This risk has been proposed as a factor infavourof higher depth sequencingstrategies. Here we report a case where barely 30-fold depth whole genome sequencing through the 100,000 Genomes Project identified low grade mosaicismthat had been missed by conventional Sanger sequencing.