Automating biomedical data science through tree-based pipeline optimization

Over the past decade, data science and machine learning has grown from a mysterious art form to a staple tool across a variety of fields in academia, business, and government. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the most tedious parts of machine learning---pipeline design. We implement a Tree-based Pipeline Optimization Tool (TPOT) and demonstrate its effectiveness on a series of simulated and real-world genetic data sets. In particular, we show that TPOT can build machine learning pipelines that achieve competitive classification accuracy and discover novel pipeline operators---such as synthetic feature constructors---that significantly improve classification accuracy on these data sets. We also highlight the current challenges to pipeline optimization, such as the tendency to produce pipelines that overfit the data, and suggest future research paths to overcome these challenges. As such, this work represents an early step toward fully automating machine learning pipeline design.Comment: 16 pages, 5 figures, to appear in EvoBIO 2016 proceeding

State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016–2018

Objective: To provide a snapshot of the profile of adults and youth with type 1 diabetes (T1D) in the United States and assessment of longitudinal changes in T1D management and clinical outcomes in the T1D Exchange registry. Research Design and Methods: Data on diabetes management and outcomes from 22,697 registry participants (age 1–93 years) were collected between 2016 and 2018 and compared with data collected in 2010–2012 for 25,529 registry participants. Results: Mean HbA1c in 2016–2018 increased from 65 mmol/mol at the age of 5 years to 78 mmol/mol between ages 15 and 18, with a decrease to 64 mmol/mol by age 28 and 58–63 mmol/mol beyond age 30. The American Diabetes Association (ADA) HbA1c goal of 10-fold in children <12 years old. HbA1c levels were lower in CGM users than nonusers. Severe hypoglycemia was most frequent in participants ≥50 years old and diabetic ketoacidosis was most common in adolescents and young adults. Racial differences were evident in use of pumps and CGM and HbA1c levels. Conclusions: Data from the T1D Exchange registry demonstrate that only a minority of adults and youth with T1D in the United States achieve ADA goals for HbA1c

Hemoglobin A1c (HbA1c) changes over time among adolescent and young adult participants in the T1D exchange clinic registry

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/122422/1/pedi12295_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/122422/2/pedi12295.pd

Dissatisfied with Life or with Being Interviewed? Happiness and Motivation to Participate in a Survey

Information on the number of interviewer contacts allows insights into how people's responses to questions on happiness are connected to the difficulty of reaching potential participants. Using the paradata of the German Socio-Economic Panel Study (SOEP), this paper continues such research by revealing a strong link between respondent motivation and reported happiness. Analyses of responses by future non-respondents substantiate this finding and shed light on a key question for empirical research on subjective well-being, which is whether the unhappy tend to avoid survey participation or whether the unwilling might respond more negatively when being asked about their satisfaction with life

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups

Background: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method: Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Acquired Resistance to KRAS (G12C) Inhibition in Cancer

BACKGROUND: Clinical trials of the KRAS inhibitors adagrasib and sotorasib have shown promising activity in cancers harboring KRAS glycine-to-cysteine amino acid substitutions at codon 12 (KRAS(G12C)). The mechanisms of acquired resistance to these therapies are currently unknown. METHODS: Among patients with KRAS(G12C) -mutant cancers treated with adagrasib monotherapy, we performed genomic and histologic analyses that compared pretreatment samples with those obtained after the development of resistance. Cell-based experiments were conducted to study mutations that confer resistance to KRAS(G12C) inhibitors. RESULTS: A total of 38 patients were included in this study: 27 with non-small-cell lung cancer, 10 with colorectal cancer, and 1 with appendiceal cancer. Putative mechanisms of resistance to adagrasib were detected in 17 patients (45% of the cohort), of whom 7 (18% of the cohort) had multiple coincident mechanisms. Acquired KRAS alterations included G12D/R/V/W, G13D, Q61H, R68S, H95D/Q/R, Y96C, and high-level amplification of the KRAS(G12C) allele. Acquired bypass mechanisms of resistance included MET amplification; activating mutations in NRAS, BRAF, MAP2K1, and RET; oncogenic fusions involving ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN. In two of nine patients with lung adenocarcinoma for whom paired tissue-biopsy samples were available, histologic transformation to squamous-cell carcinoma was observed without identification of any other resistance mechanisms. Using an in vitro deep mutational scanning screen, we systematically defined the landscape of KRAS mutations that confer resistance to KRAS(G12C) inhibitors. CONCLUSIONS: Diverse genomic and histologic mechanisms impart resistance to covalent KRAS(G12C) inhibitors, and new therapeutic strategies are required to delay and overcome this drug resistance in patients with cancer. (Funded by Mirati Therapeutics and others; ClinicalTrials.gov number, NCT03785249.)

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10–8 as genome-wide significant, and p-values < 1 × 10–5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10–7), which showed genome-wide significant interaction (p-value = 3.8 × 10–8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen–progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Rare germline copy number variants (CNVs) and breast cancer risk.

Funder: CIHRGermline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance

Particulate matter exposure during pregnancy is associated with birth weight, but not gestational age, 1962-1992: a cohort study

<p>Abstract</p> <p>Background</p> <p>Exposure to air pollutants is suggested to adversely affect fetal growth, but the evidence remains inconsistent in relation to specific outcomes and exposure windows.</p> <p>Methods</p> <p>Using birth records from the two major maternity hospitals in Newcastle upon Tyne in northern England between 1961 and 1992, we constructed a database of all births to mothers resident within the city. Weekly black smoke exposure levels from routine data recorded at 20 air pollution monitoring stations were obtained and individual exposures were estimated via a two-stage modeling strategy, incorporating temporally and spatially varying covariates. Regression analyses, including 88,679 births, assessed potential associations between exposure to black smoke and birth weight, gestational age and birth weight standardized for gestational age and sex.</p> <p>Results</p> <p>Significant associations were seen between black smoke and both standardized and unstandardized birth weight, but not for gestational age when adjusted for potential confounders. Not all associations were linear. For an increase in whole pregnancy black smoke exposure, from the 1^st(7.4 μg/m³) to the 25^th(17.2 μg/m³), 50^th(33.8 μg/m³), 75^th(108.3 μg/m³), and 90^th(180.8 μg/m³) percentiles, the adjusted estimated decreases in birth weight were 33 g (SE 1.05), 62 g (1.63), 98 g (2.26) and 109 g (2.44) respectively. A significant interaction was observed between socio-economic deprivation and black smoke on both standardized and unstandardized birth weight with increasing effects of black smoke in reducing birth weight seen with increasing socio-economic disadvantage.</p> <p>Conclusions</p> <p>The findings of this study progress the hypothesis that the association between black smoke and birth weight may be mediated through intrauterine growth restriction. The associations between black smoke and birth weight were of the same order of magnitude as those reported for passive smoking. These findings add to the growing evidence of the harmful effects of air pollution on birth outcomes.</p