Literature DB >> 25166427

Return of individual genetic results in a high-risk sample: enthusiasm and positive behavioral change.

Sarah M Hartz1, Emily Olfson1, Robert Culverhouse1, Patricia Cavazos-Rehg1, Li-Shiun Chen1, James DuBois1, Sherri Fisher1, Kimberly Kaphingst1, David Kaufman2, Andrew Plunk1, Shelina Ramnarine1, Stephanie Solomon3, Nancy L Saccone1, Laura J Bierut1.   

Abstract

PURPOSE: The goal of this study was to examine participant responses to disclosure of genetic results in a minority population at high risk for depression and anxiety.
METHODS: Eighty-two subjects in a genetic study of nicotine dependence were offered personalized genetic results. All were nicotine-dependent and 64% self-identified as African American. Pathway Genomics was used to evaluate genetic risks for five complex diseases. Participants returned 4-8 weeks after enrollment for in-person genetic counseling interviews and evaluation of baseline measures. A telephone follow-up was performed 4-8 weeks later to assess responses to results.
RESULTS: Fifty of the 82 subjects (61%) were interested in receiving genetic results. These participants had multiple risk factors, including high baseline measures of depression (66%) and anxiety (32%), as well as low rates of employment (46%), adequate health literacy (46%), and health insurance (45%). Pathway Genomics reported "increased risk" for at least one disease in 77% of subjects. Ninety-five percent of participants reported that they appreciated the genetic results, and receiving these results was not associated with changes in symptoms of depression or anxiety. Furthermore, after return of genetic results, smoking cessation attempts increased (P = 0.003).
CONCLUSION: Even in an underserved population at high risk for adverse psychological reactions, subjects responded positively to personalized genetic results.

Entities:  

Mesh:

Year:  2014        PMID: 25166427      PMCID: PMC4344933          DOI: 10.1038/gim.2014.110

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


INTRODUCTION

Over the last decade, the return of individual genetic research results has emerged as a highly contentious issue [1-5]. Advocates assert that researchers and clinicians have an ethical obligation to offer certain results when possible, based on principles of beneficence and respect of persons [1,2]. Critics emphasize possible harmful effects, including therapeutic misconceptions, financial burdens, and undue anxieties [1,3,4]. Similar concerns regarding potential downstream consequences of individual genetic results have been raised in consumer settings with the increased use of personalized genetic testing, especially for direct-to-consumer companies [6-10]. As genomics research marches forward, a better understanding of how individuals respond to personalized genetic results is critical for informing future policies and decisions regarding appropriate use of this information. There has been recent controversy with direct to consumer genetic testing. Specifically, the FDA issued concerns that 23andMe was inappropriately offering genetic-based medical recommendations[11]. Because of this, 23andMe stopped offering medical reports with the genetic testing. Rather, 23andMe offers the same genetic testing and ancestry report, but no medical reports. Despite the controversy with 23andMe, studies demonstrate that the public strongly favors opportunities for disclosure of individual genetic results [12-17]. Although African Americans are often under-represented in genetics research, focus groups indicate that many individuals are interested in receiving their genetic results [12,14], and offering results may encourage future research participation [14]. In response to the public’s interest in individualized genetic information, a growing number of studies over the last five years have examined subject responses to actually receiving genetic findings [18-24]. These studies suggest that return of genetic results does not pose substantial psychological or behavioral harms. Because these studies focused primarily on populations that are at relatively low-risk for adverse psychological reactions (majority college-educated European Americans with health insurance, who are employed or retired), the generalizability of these positive findings remains unclear. An important next step is to investigate participant responses to personalized genetic results in a population at high-risk for adverse psychological reactions. In this study, individual research results on complex disease risks were returned to participants in a genetic study of nicotine dependence: the majority of participants were African American, not college educated, unemployed, and uninsured. These data provide critical insight into the psychological and behavioral impact of personalized genetic results in a population that has traditionally been severely underrepresented in genetics research.

MATERIALS AND METHODS

SETTING AND PARTICIPANTS

This return of results study builds upon an ongoing genetic study of nicotine dependence, the Collaborative Genetic Study of Nicotine Dependence (COGEND) [25,26]. In 2013, COGEND was recruiting nicotine-dependent smokers from the St. Louis metropolitan area. All nicotine-dependent COGEND subjects were eligible for this return of results study until 50 subjects were recruited. After completion of the COGEND interview, eligible subjects interested in participating in this return of results study were read basic explanations of the genetic testing procedures and the interpretation of genetic results. Those who expressed continued interest were given a complete description of the study design, including example genetic results (Supplementary Material). Individuals who chose to be study participants then signed an informed consent form. This study protocol was approved by the Institutional Review Board at Washington University School of Medicine.

STUDY DESIGN

Participants were assessed three times: at the time of consent, prior to receiving genetic results (4–8 weeks after consent), and at a telephone follow-up (4–8 weeks after return of genetic results and genetic counseling). At the time of consent, participants were assessed for anxiety using the Beck Anxiety Inventory (BAI)[27] and depressive symptoms using the Center for Epidemiological Studies Depression Scale (CES-D)[28]. Participants donated saliva samples, which were sent to Pathway Genomics (San Diego, CA, USA) for micro-array-based genetic analysis of risk for five complex diseases: lung cancer, breast or prostate cancer, colorectal cancer, heart attack, and type II diabetes (example results are given in the Supplementary Material). Pathway Genomics genotyped the saliva sample for known genetic variants related to these diseases and used a proprietary algorithm to define individuals as “increased risk”, “above-average risk”, and “average risk”. Pathway Genomics was chosen for this return of results study because it is accredited in accordance with the U.S. Health and Human Services Clinical Laboratory Improvement Amendments (CLIA) of 1988 and therefore meets basic standards for return of results. Genotyping from the original parent study of nicotine dependence was not performed in a CLIA certified lab. We chose to return genetic results of five complex diseases, for which smoking cessation is critical for reducing overall risk. Of note, the strongest genetic risk factor for lung cancer is the same as the strongest genetic risk for smoking behavior. Pathway Genomics does not offer reports on nicotine addiction. Participants returned 4–8 weeks after donating samples to receive their genetic results. At the beginning of this meeting, each participant was assessed for health literacy using the REALM-R [29]. Current healthcare accessibility, smoking behavior, cessation attempts, diet, and exercise were also assessed. Subsequently, the results were given to the participant in the context of a genetic counseling session. Although genetic counselors were given up to an hour to meet with each subject, the average counseling session lasted approximately 10 minutes. The genetic counselor gave personalized results to each participant, and emphasized the importance of smoking cessation. The counselor then offered to answer any questions the subjects had about their results. Before leaving, subjects were given a folder containing individual genetic results (without identifying information), and smoking cessation tips. Each participant was called on the telephone 4–8 weeks after receiving the genetic results and asked about his or her response to the results, as well as current healthcare accessibility, smoking behavior, diet, exercise, symptoms of depression (CES-D)[28] and symptoms of anxiety (BAI)[27].

STATISTICAL ANALYSIS

All statistical analyses were performed using Statistical Analysis System (SAS 9.3, Cary, NC, USA). Changes in dichotomous variables over time (depression, anxiety, smoking cessation attempts in past month) were evaluated using McNemar’s test, and changes in continuous variables (change in depression and anxiety scales) were modeled using linear regression. Power calculations (SAS PROC POWER) were also employed.

RESULTS

PARTICIPANT CHARACTERISTICS

82 subjects were offered return of genetic results. 61% (50/82) of these subjects accepted the invitation to participate (Figure 1). Of the 32 subjects who declined participation, 41% (13/32) reported scheduling conflicts. No statistical differences between the participants (n=50) and non-participants (n=32) were observed (p>0.05) for sex, race, educational attainment, employment status or age (details of demographics in Table 1).
Figure 1

Flowchart of subject participation

Table 1

Characteristics of subjects offered genetic results

ParticipantsN=50Non-participantsN=32
Average age (SD)34.9 (5.8)33.3 (5.5)
Male46%47%
African American62%44%
Bachelor’s Degree or Associate’s Degree30%23%
Employed46%50%
Has health insurance45%-
Limited health literacy54%-
Baseline depression (CES-D ≥16)66%-
Baseline anxiety (BAI ≥16)32%-

no statistical difference between participants and non-participants (p>0.05)

The participants themselves were at very high risk for psychiatric events (Table 1). Specifically, their baseline symptoms of depression and anxiety (strong predictors of future major depression disorder and anxiety [30]) were very high. In addition, many subjects had limited health literacy, had low education, were unemployed, or were uninsured (Table 1). These factors increase the chance of confusion or distress, which may in turn increase the risk for depression or anxiety.

GENETIC RESULTS

The participants reported an overwhelmingly positive reaction to the results: 95% of the subjects said they found the results worthwhile. All but one subject discussed the results with someone outside the study, including his/her doctor (17%) and family or friends (95%). Most of the subjects (77%, 33/43) received a genetic report with “increased risk” for at least one of the five tested diseases. The most common disease with increased risk was colorectal cancer (16/43). None of the women received a report stating increased risk for breast cancer (BRCA1 and BRCA2 variants were not genotyped, Supplementary Material). Two subjects reported being upset by the results. Both of these subjects had “above average” risk for lung cancer; one also had “above average” risk for heart disease. Both found the results worthwhile, both told their friends about the results, and neither had clinically significant increase in anxiety.

CHANGES IN DEPRESSION AND ANXIETY

Receiving genetic results did not lead to changes in the proportion of subjects meeting criteria for depression as defined by CES-D ≥ 16, or anxiety as defined by BAI ≥ 16 (Table 2). In addition, even for individuals who received reports indicating increased risk of any disease or each specific disease, we observed no significant increase in the overall proportion of subjects with depression or anxiety (Table 2).
Table 2

Return of genetic results does not increase the proportion of subjects with depression or anxiety.

Depression (CES-D ≥16)Anxiety (BAI ≥16)
NBaselineFollow-upp-valueBaselineFollow-upp-value
Full Sample4366%73%0.5532%27%0.69
Subjects at increased genetic risk for:
 Any Diagnosis3363%76%0.2130%27%0.65
 Lung Cancer771%71%1.029%29%1.0
 Heart Attack967%67%1.033%22%0.32
 Type II Diabetes667%83%0.3217%17%1.0
 Colorectal Cancer1656%75%0.2625%31%0.32
 Prostate Cancer887%75%0.3238%38%1.0
 Breast Cancer0------
To further investigate the impact of receiving genetic results on symptoms of depression and anxiety, we evaluated whether increased risk of disease was related to change in depression or anxiety scores (Table 3). No associations were seen between changes in depression or anxiety scores and reported genetic risk of disease (Table 3).
Table 3

Anxiety and depression scores are not clinically increased by return of genetic results, even when there is increased risk for disease.

Depression scale (CES-D)Anxiety scale (BAI)
NAverage change in scorep-valueAverage change in scorep-value
Full Sample*430.50.752.90.10
Average change in score based on increased genetic risk for:
 Any Diagnosis331.70.153.90.24
 Lung Cancer7−4.00.356.30.58
 Heart Attack93.10.253.10.94
 Type II Diabetes62.30.747.20.55
 Colorectal Cancer162.30.405.20.27
 Prostate Cancer8−0.50.721.10.64
 Breast Cancer0----

Clinically significant change for both scales (BAI and CES-D) is 6.

With current sample size and standard error, there is 89% power to detect an overall increase of 6 in CES-D score, and 97% power to detect an overall increase of 6 in BAI score for p<0.05.

A power analysis was used to determine whether lack of a statistical association suggests lack of a clinical association. A clinically significant increase in symptoms of depression was defined as an increased CES-D score of 6, which corresponds to two symptoms of depression increasing from “rarely” to “most or all of the time”. Similarly, a clinically significant increase in symptoms of anxiety was defined as an increase in BAI score of 6, which corresponds to anxiety increasing from “no anxiety” to “mild anxiety”, or “mild anxiety” to “moderate anxiety”. Using the observed sample size and standard error, we calculated that there was 89% power to detect a clinically significant change in depression, and 97% power to detect a clinically significant change in anxiety. This suggests that we had adequate power to detect clinically significant effects in the overall sample.

BEHAVIORAL RESPONSE

Our secondary analyses examined whether return of genetic results changed behavior. Attempts at smoking cessation were measured at two time points: a baseline of 4–8 weeks after the parent genetic study of nicotine dependence (at the time of genetic counseling), and a follow-up of 4–8 weeks after genetic counseling for the return of results study (Table 4). Subjects were more likely to attempt smoking cessation after receiving genetic results relative to a similar duration of time after participation in the study of nicotine dependence alone (p=0.003). A strong increase in quit attempts occurred among individuals who received reports with increased genetic risk for lung cancer (quit attempts increased from 14% to 57%), but this difference was not statistically significant (p=0.08).
Table 4

Smoking cessation attempts increased following the return of personalized genetic results.

Attempted smoking cessation in past month
NBaselineFollow-upp-value
Full Sample4321%53%0.0005
Subjects at increased genetic risk for:
 Any Diagnosis3324%52%0.003
 Lung Cancer714%57%0.08
 Heart Attack922%33%0.32
 Type II Diabetes633%67%0.15
 Colorectal Cancer1625%50%0.05
 Prostate Cancer838%63%0.15
 Breast Cancer0---

DISCUSSION

After receiving personalized genetic results, participants from a genetic study of nicotine dependence reported that the results were useful, they did not experience an increase in symptoms of depression or anxiety. This overall positive response to return of genetic results is particularly noteworthy because the sample is comprised of underserved individuals at high-risk for adverse psychological events, as evidenced by high rates of baseline symptoms of depression and anxiety, as well as low rates of employment, health insurance, and health literacy. Overall, this study had a high participation rate (61%) and almost all of the participants indicated that receiving genetic results was worthwhile (95%), suggesting that individuals from minority high-risk populations appreciate personalized genetic findings. This extends results from focus groups, which found that the majority of African Americans were interested in receiving genetic results [12,14]. Participants did not have increased scores on depression and anxiety measures in response to receiving genetic risk information on complex diseases, similar to studies of other populations at relatively lower risk for adverse events [18,23]. Bloss et al. offered subsidized personalized genetic testing of complex diseases to individuals working in health and technology, and responses from over 2,000 participants showed no measurable changes in anxiety 3 months after receiving genetic information [18]. In addition, preliminary findings from a survey of 1,800 customers of two genomics companies suggest no elevation in anxiety or distress during the year after receiving genetic results [23]. Our findings build on these studies by demonstrating that even in a high-risk population defined by low health care literacy, high levels of unemployment and lack of insurance, symptoms of depression and anxiety were not raised after disclosure of genetic complex disease information. Beyond not causing substantial increase in symptoms of depression or anxiety, after disclosure of genetic risks for complex diseases, there was an increase in smoking cessation attempts. This raises the question whether return of genetics results may motivate smoking cessation attempts in a nicotine dependent population, contributing to the debate over whether genetic information can motivate risk-reducing health behaviors [31]. Specifically, subjects were significantly more likely to make quit attempts 4–8 weeks following return of results in the genetic counseling session as compared to a baseline measured 4–8 weeks following the original interview for the parent study of nicotine dependence. This finding suggests that the smoking behavioral change was driven by the process of receiving personalized genetic results and not simply interviewer contact or discussion about smoking cessation. However, further studies that include a control group are necessary to determine whether increased quit attempts are due to receiving personalized genetic results rather than confounding factors, such as increased study engagement. Even though we observed an increase in smoking quit attempts, cessation is difficult, and often numerous attempts are made before smokers are able to successfully quit. A recent meta-analysis found that communication of DNA-based risk estimates was not associated with smoking cessation [32]. However, we can speculate that increased motivation to quit during the period following return of genetic results may be an opportune time for intensive smoking cessation therapies. This study has several limitations. First, we used a convenience sample recruited through a parent study of nicotine dependence, and our study did not include a control group. Second, the sample size of 50 participants is modest, and therefore the observed results may be driven by a limited number of individuals. Nonetheless, the study was appropriately powered to detect clinically significant changes in symptoms of depression and anxiety (89% and 97%, respectively). Third, we returned genetic risk results of five complex diseases and did not include highly penetrant genetic variants, such as BRCA1 or BRCA2 mutations. It is possible that results associated with a greater increased risk of disease may prompt additional distress. Studies that returned pathogenic variants in APOE for Alzheimer’s disease [20], BRCA1 and BRCA2 for hereditary breast and ovarian cancer [19], and CDKN2A for melanoma [24] found that these potentially alarming disclosures caused only modest distress. Additional studies are necessary to extend these analyses to underserved and high-risk populations. Fourth, our findings are based on a single follow-up assessment at 1–2 months and cannot be used to assess the long-term effects of the genetic results. In addition, it would be useful to expand the qualitative component of this study. Future qualitative and quantitative studies that follow research participants after receiving genetic results are needed to better understand their perceptions of genetic risk and how it shapes health outcomes over the long term.

CONCLUSION

This study lays the foundation for understanding how high-risk underserved populations respond to personalized genetic results, informing the debate surrounding the consequences of returning these results. Specifically, we demonstrate that similar to other populations, high-risk minority participants appreciate return of results, do not have increased symptoms of depression or anxiety, and may benefit from receiving individual genetic information. Technical and scientific barriers regarding the disclosure of genetic results in research, clinical, and consumer settings still exist, and overcoming them will require continued progress in several areas: definitive identification and characterization of genetic risk factors, validation of algorithms to estimate risk, and development of standardized policies and procedures to prioritize and communicate genetic information. The empirical evidence presented in this study suggests that, once these barriers are crossed, personalized genetic results may be positively received in underserved populations.
  29 in total

1.  Risks and benefits of direct-to-consumer genetic testing remain unclear.

Authors:  Bridget M Kuehn
Journal:  JAMA       Date:  2008-10-01       Impact factor: 56.272

2.  Regulation: The FDA is overcautious on consumer genomics.

Authors:  Robert C Green; Nita A Farahany
Journal:  Nature       Date:  2014-01-16       Impact factor: 49.962

3.  An inventory for measuring clinical anxiety: psychometric properties.

Authors:  A T Beck; N Epstein; G Brown; R A Steer
Journal:  J Consult Clin Psychol       Date:  1988-12

4.  Communication of biobanks' research results: what do (potential) participants want?

Authors:  Tineke M Meulenkamp; Sjef K Gevers; Jasper A Bovenberg; Gerard H Koppelman; Astrid van Hylckama Vlieg; Ellen M A Smets
Journal:  Am J Med Genet A       Date:  2010-10       Impact factor: 2.802

5.  A shortened instrument for literacy screening.

Authors:  Pat F Bass; John F Wilson; Charles H Griffith
Journal:  J Gen Intern Med       Date:  2003-12       Impact factor: 5.128

6.  Disclosure of APOE genotype for risk of Alzheimer's disease.

Authors:  Robert C Green; J Scott Roberts; L Adrienne Cupples; Norman R Relkin; Peter J Whitehouse; Tamsen Brown; Susan LaRusse Eckert; Melissa Butson; A Dessa Sadovnick; Kimberly A Quaid; Clara Chen; Robert Cook-Deegan; Lindsay A Farrer
Journal:  N Engl J Med       Date:  2009-07-16       Impact factor: 91.245

7.  Multiple independent loci at chromosome 15q25.1 affect smoking quantity: a meta-analysis and comparison with lung cancer and COPD.

Authors:  Nancy L Saccone; Robert C Culverhouse; Tae-Hwi Schwantes-An; Dale S Cannon; Xiangning Chen; Sven Cichon; Ina Giegling; Shizhong Han; Younghun Han; Kaisu Keskitalo-Vuokko; Xiangyang Kong; Maria Teresa Landi; Jennie Z Ma; Susan E Short; Sarah H Stephens; Victoria L Stevens; Lingwei Sun; Yufei Wang; Angela S Wenzlaff; Steven H Aggen; Naomi Breslau; Peter Broderick; Nilanjan Chatterjee; Jingchun Chen; Andrew C Heath; Markku Heliövaara; Nicole R Hoft; David J Hunter; Majken K Jensen; Nicholas G Martin; Grant W Montgomery; Tianhua Niu; Thomas J Payne; Leena Peltonen; Michele L Pergadia; John P Rice; Richard Sherva; Margaret R Spitz; Juzhong Sun; Jen C Wang; Robert B Weiss; William Wheeler; Stephanie H Witt; Bao-Zhu Yang; Neil E Caporaso; Marissa A Ehringer; Tim Eisen; Susan M Gapstur; Joel Gelernter; Richard Houlston; Jaakko Kaprio; Kenneth S Kendler; Peter Kraft; Mark F Leppert; Ming D Li; Pamela A F Madden; Markus M Nöthen; Sreekumar Pillai; Marcella Rietschel; Dan Rujescu; Ann Schwartz; Christopher I Amos; Laura J Bierut
Journal:  PLoS Genet       Date:  2010-08-05       Impact factor: 5.917

8.  Public expectations for return of results from large-cohort genetic research.

Authors:  Juli Murphy; Joan Scott; David Kaufman; Gail Geller; Lisa LeRoy; Kathy Hudson
Journal:  Am J Bioeth       Date:  2008-11       Impact factor: 11.229

9.  Public preferences regarding the return of individual genetic research results: findings from a qualitative focus group study.

Authors:  Juli Murphy Bollinger; Joan Scott; Rachel Dvoskin; David Kaufman
Journal:  Genet Med       Date:  2012-03-08       Impact factor: 8.822

10.  Subjects matter: a survey of public opinions about a large genetic cohort study.

Authors:  David Kaufman; Juli Murphy; Joan Scott; Kathy Hudson
Journal:  Genet Med       Date:  2008-11       Impact factor: 8.822

View more
  15 in total

1.  Reconceptualizing harms and benefits in the genomic age.

Authors:  Anya E R Prince; Benjamin E Berkman
Journal:  Per Med       Date:  2018-09-27       Impact factor: 2.512

2.  Implications of Personal Genomic Testing for Health Behaviors: The Case of Smoking.

Authors:  Emily Olfson; Sarah Hartz; Deanna Alexis Carere; Robert C Green; J Scott Roberts; Laura J Bierut
Journal:  Nicotine Tob Res       Date:  2016-07-12       Impact factor: 4.244

Review 3.  Preparing the Way: Exploiting Genomic Medicine to Stop Smoking.

Authors:  Laura J Bierut; Rachel F Tyndale
Journal:  Trends Mol Med       Date:  2018-01-04       Impact factor: 11.951

4.  Attitudes toward Precision Treatment of Smoking in the Southern Community Cohort Study.

Authors:  Nicole Senft; Maureen Sanderson; Rebecca Selove; William J Blot; Stephen King; Karen Gilliam; Suman Kundu; Mark Steinwandel; Sarah J Sternlieb; Shaneda Warren Andersen; Debra L Friedman; Erin Connors; Mary Kay Fadden; Matthew Freiberg; Quinn S Wells; Juan Canedo; Rachel F Tyndale; Robert P Young; Raewyn J Hopkins; Hilary A Tindle
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-06-03       Impact factor: 4.254

5.  "I don't believe it." Acceptance and skepticism of genetic health information among African-American and White smokers.

Authors:  Erika A Waters; Linda Ball; Sarah Gehlert
Journal:  Soc Sci Med       Date:  2017-05-03       Impact factor: 4.634

6.  A Clinical Service to Support the Return of Secondary Genomic Findings in Human Research.

Authors:  Andrew J Darnell; Howard Austin; David A Bluemke; Richard O Cannon; Kenneth Fischbeck; William Gahl; David Goldman; Christine Grady; Mark H Greene; Steven M Holland; Sara Chandros Hull; Forbes D Porter; David Resnik; Wendy S Rubinstein; Leslie G Biesecker
Journal:  Am J Hum Genet       Date:  2016-03-03       Impact factor: 11.025

7.  Participatory Design of a Personalized Genetic Risk Tool to Promote Behavioral Health.

Authors:  Alex T Ramsey; Michael Bray; Penina Acayo Laker; Jessica L Bourdon; Amelia Dorsey; Maia Zalik; Amanda Pietka; Patricia Salyer; Erika A Waters; Li-Shiun Chen; Laura J Bierut
Journal:  Cancer Prev Res (Phila)       Date:  2020-03-24

8.  Most Current Smokers Desire Genetic Susceptibility Testing and Genetically-Efficacious Medication.

Authors:  Ami Chiu; Sarah Hartz; Nina Smock; Jingling Chen; Amaan Qazi; Jeffrey Onyeador; Alex T Ramsey; Laura J Bierut; Li-Shiun Chen
Journal:  J Neuroimmune Pharmacol       Date:  2018-10-29       Impact factor: 4.147

9.  Proof of Concept of a Personalized Genetic Risk Tool to Promote Smoking Cessation: High Acceptability and Reduced Cigarette Smoking.

Authors:  Alex T Ramsey; Jessica L Bourdon; Michael Bray; Amelia Dorsey; Maia Zalik; Amanda Pietka; Patricia Salyer; Li-Shiun Chen; Timothy B Baker; Marcus R Munafò; Laura J Bierut
Journal:  Cancer Prev Res (Phila)       Date:  2020-09-21

10.  Effects of participation in a U.S. trial of newborn genomic sequencing on parents at risk for depression.

Authors:  Talia S Schwartz; Kurt D Christensen; Melissa K Uveges; Susan E Waisbren; Amy L McGuire; Stacey Pereira; Jill O Robinson; Alan H Beggs; Robert C Green; Gloria A Bachmann; Arnold B Rabson; Ingrid A Holm
Journal:  J Genet Couns       Date:  2021-07-26       Impact factor: 2.537

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.