Exploring Genetic Testing for Rare Disorders of Obesity: Experience and Perspectives of Pediatric Weight Management Providers

Abstract

Background:

This study describes experiences and perspectives of pediatric weight management (PWM) providers on the implementation of genetic testing for rare causes of obesity.

Methods:

Purposive and snowball sampling recruited PWM providers via email to complete a 23-question survey with multiple choice and open-ended questions. Analyses include descriptive statistics, Fisher's exact test, one-way ANOVA with Tukey's post hoc test, and qualitative analysis.

Results:

Of the 55 respondents, 80% reported ordering genetic testing. Respondents were primarily physicians (82.8%) in practice for 11–20 years (42%), identified as female (80%), White (76.4%), and non-Hispanic (92.7%) and provided PWM care 1–4 half day sessions per week. Frequently reported patient characteristics that prompted testing did not vary by provider years of experience (YOE). These included obesity onset before age 6, hyperphagia, dysmorphic facies, and developmental delays. The number of patient characteristics that prompted testing varied by YOE (p = 0.03); respondents with 6–10 YOE indicated more patient characteristics than respondents with >20 YOE (mean 10.3 vs. mean 6.2). The reported primary benefit of testing was health information for patients/families; the primary drawback was the high number of indeterminate tests. Ethical concerns expressed were fear of increasing weight stigma, discrimination, and impact on insurance coverage. Respondents (42%) desired training and guidance on interpreting results and counseling patients and families.

Conclusions:

Most PWM providers reported genetic testing as an option for patient management. Provider training in genetics/genomics and research into provider and family attitudes on the genetics of obesity and the value of genetic testing are next steps to consider.

Introduction

The heterogeneity of responses to treatment in obesity care is leading providers to individualize therapies for patients.¹ Increased accessibility to genetic genomic testing allows use of personalized genomic medicine for prevention, diagnosis, and treatment of disease based on genetic makeup, lifestyle, and environment.^2,3 Considerable knowledge gaps exist about organizational requirements and clinician and patient needs for translation of genomic medicine to clinical practice.^4,5 The frequency of genomic testing has increased in contexts such as cancer risk prediction and treatment, neurodevelopmental conditions, and pharmacogenomics.⁶ However, all clinicians are not currently prepared to communicate nuanced genetic findings.² Further, while targeted therapies are evolving, clinicians need to understand how to contextualize genetic results, given the availability and utility of therapy options, and communicate this to their patients.

Rare genetic forms of obesity account for 5%–13% of early onset obesity in children and are poorly understood and underdiagnosed.^7,8 The American Academy of Pediatrics clinical guidelines for evaluation and treatment of obesity include assessment for genetic causes of obesity (which may include genetic testing), especially those with obesity onset ≤5 years, hyperphagia, developmental delay, syndromic features, or short stature.⁹ In certain cases, the identification of genetic causes of obesity may result in treatment, for example, Setmelanotide for leptin-melanocortin pathway or Bardet Biedl syndrome.¹⁰ The Pediatric Endocrine Society recommends testing for genetic causes of obesity in children who present with severe obesity before age 5, hyperphagia, or family history of severe obesity.¹¹ Additional features that support genetic testing include developmental delay, dysmorphic features, hormonal deficiencies, congenital anomalies, or vision loss.

The availability of genetic testing for rare disorders of obesity has evolved over time. Less than a decade ago, the available testing was assessment of leptin deficiency or resistance and single gene testing for MC4R. With advances in genetic testing technology, panel testing for many diseases (including genetic causes of obesity) is available from several commercial sources. The availability of sponsored genetic testing from Rhythm^® Pharmaceuticals https://www.preventiongenetics.com/sponsoredTesting/Rhythm/ has improved access to genetic testing for obesity to all pediatric weight management (PWM) providers.¹² We have previously shown that genetic screening for children with obesity in the absence of syndromic features is not routinely used in PWM.¹³ Based on informal discussions with PWM providers we wanted to understand what barriers exist in logistics of testing, result interpretation, and communication of the results.

Thus, we designed this study to understand the experiences and perspectives of PWM providers on the implementation of genetic testing in pediatric obesity management.

Methods

Design, Participants, and Data Collection

In this cross sectional, mixed methods exploratory descriptive study,¹⁴ purposive sampling was used to recruit providers [Doctor of Medicine (MD), Doctor of Osteopathic Medicine (DO), Advance Practice Nurses (APN) and Physician Assistants (PA)] of PWM via email listserv after approval from Childhood Obesity Multi-Program Analysis and Study System (COMPASS) (n ≈ 90), and through publicly available email addresses of providers of PWM (n ≈ 150) at children's hospitals across all regions in the United States (via Google search). In addition, snowball sampling was used by requesting that participants forward the email to colleagues.

The survey was conducted through Qualtrics between November 15, 2022, and March 30, 2023. An introduction of the study, link to the survey, and invitation to participate was distributed to potential participants via email with three follow-up reminders. No identifiable information was collected, and the responses remained anonymous. The University of Wisconsin Milwaukee Institutional Review Board deemed this study as exempt (Protocol No. 23.039).

Measures

A 23-question self-administered survey was developed to assess the current practices and experiences in genetic testing for rare disorders of obesity of providers of PWM (Supplementary Table S1). Survey development was guided by our previous work, and a review of the literature.¹³ The survey was developed by K.J.R., revised with feedback from all authors, and piloted with six providers. Cognitive interviewing was not undertaken. The questionnaire domains included the following: (1) demographics, provider years of experience (YOE) groups (from the terminal degree), number of clinical sessions for weight management care per week (categorical); (2) current genetic testing routines and rationale for testing (multiple choice); (3) coordination, tracking, and communication of test results (multiple choice); and (4) opinions on benefits, challenges, and ethics of testing (open ended).

Data Analysis

Analyses were completed using SAS 9.4 (Cary, NC). Due to the small sample size, Fisher's exact test was used to examine the association between provider YOE groups and the individual patient characteristics used in the decision to perform genetic testing. One-way ANOVA and Tukey's post hoc test were used to compare the average number of patient characteristics that prompted testing and YOE groups, and to examine where the average number of patient characteristics differed between YOE groups, respectively. Two authors (K.J.R. and E.C.) with expertise in qualitative analysis used conventional content analysis for the five open ended questions.¹⁵ Both authors independently completed initial coding and application of themes on all these data. K.J.R. and E.C. then met and together completed a comparative analysis with final codes and themes reached through consensus.^14,15

Results

Participant Characteristics and Testing Practices

A total of 58 responses were collected with 2 individuals excluded for not being a primary provider, that is, MD/DO, APN, or PA, and 1 individual who did not complete the survey. Participants in analyses (n = 55) were primarily physicians (82.8%), female (80.0%), White (76.4%), non-Hispanic (92.7%), and between 41 and 60 years of age (61.8%). Forty percent of participants reported 11–20 YOE and most (80%) provided 1–4 half day clinical sessions/week for weight management. Most participants (80%) reported performing genetic testing for rare disorders of obesity. Detailed participant characteristics and testing practices can be found in Table 1.

Table 1.

Participant Characteristics and Testing Practices (n = 55)

	n	%		n	%
Primary role			Perform genetic testing
MD/DO	48	87.3	Yes	44	80.0
APN^a	6	10.9	No	11	20.0
PA	1	1.8	Other providers in clinic testing
Gender			Yes	44	81.5
Male	11	20	No	9	16.7
Female	44	80	Don't know	1	1.8
Age, years			Missing	1	1.8
<40	15	27.3	System to track who is tested^b
41–60	34	61.8	Yes	15	34.9
60–75	6	10.9	No	28	65.1
Race			System to track testing results^b
Asian	10	18.2	Yes	15	34.9
Black	2	3.6	No	28	65.1
White	42	76.4
Multiracial	1	1.8	Where samples are processed^c
Ethnicity			Prevention Genetics-sponsored	43	78.2
Hispanic/Latinx	2	3.6	Prevention Genetics-insurance	3	5.5
Non-Hispanic/Latinx	51	92.7	Other genetic company-insurance	1	1.8
Other	1	1.8	Home institution-insurance	3	5.5
Prefer not to answer	1	1.8	Research testing	2	3.6
Provider YOE			Other	3	5.5
<5	7	12.7
5–10	12	21.8	Available resources^c
11–20	22	40.0	Handle results and treatment changes myself	29	32.2
>20	14	25.5	Referral to genetics/genetic counselor	33	36.7
Weight management care, 1/2 days/week			Genetic counselor available in my clinic	4	4.4
1–4	44	80.0	Genetic counselor through testing services	23	25.6
5–8	9	16.4	Other	1	1.1
9+	2	3.4

A total of 7 APNS initially responded, but 1 had incomplete/missing data therefore reporting is for 55 providers with complete data.

One missing response of those who test.

Multiple answers allowed.

APN, Advance Practice Nurse; DO, Doctor of Osteopathic Medicine; MD, Doctor of Medicine; PA, Physician Assistants; YOE, years of experience.

Patient Characteristics That Prompt Genetic Testing

Out of 55 participants, 20.0% (n = 11) responded that they did not perform genetic testing. Of those who did not perform testing, one respondent had <5 YOE, five had 11–20 YOE and five had >20 YOE. Respondents (n = 44) reported between one and four reasons for not ordering testing. The top reasons for not testing were “not sure whom to test and/or lacked a process to do so” (13%), “referral to genetics” (9%), or “results would not change treatment” (8%). Single responses to this question cited “ethical concerns,” “unprepared to explain the results to patients and families,” “not covered by insurance,” “do not have time,” and “the process for testing is cumbersome.”

Participants were asked to indicate the patient characteristics that would prompt genetic testing from a list of options and were allowed to choose multiple answers. There were 19 characteristics listed (Table 2) and an option to choose “other.” On average, participants identified 7.90 ± 3.92 physical characteristics. The top reasons providers chose to perform genetic testing were “early onset of obesity before age 6 years” (91%), “hyperphagia” and “dysmorphic facies” (each 76%) and “developmental delays” (69%). Of note, 52% of providers reported ordering testing due to parent or patient request and almost half ordered testing because they “just felt something isn't right” (49%).

Table 2.

Patient Characteristics Prompting Testing

What types of patient characteristics would prompt you to consider genetic screening for rare disorders of obesity?	Overall (n = 55), n (%)	YOE group				p ^a
	Overall (n = 55), n (%)	<5 years (n = 7), n (%)	6–10 years (n = 12), n (%)	11–20 years (n = 22), n (%)	>20 years (n = 14), n (%)	p ^a
Early onset obesity (before age 6)	50 (90.9)	6 (85.7)	11 (91.7)	19 (86.4)	14 (100.0)	0.460
Early onset obesity (before age 10)	8 (14.6)	1 (14.3)	3 (25.0)	4 (18.2)	0 (0.0)	0.264
Rapid unexplained weight gain (any age)	12 (21.8)	1 (14.3)	5 (41.7)	4 (18.2)	2 (14.3)	0.371
Severe obesity	33 (60.0)	3 (42.9)	8 (66.7)	15 (68.2)	7 (50.0)	0.533
Hyperphagia	42 (76.4)	7 (100.0)	10 (83.3)	16 (72.7)	9 (64.3)	0.313
Binge eating disorder	1 (1.8)	0 (0.0)	0 (0.0)	0 (0.0)	1 (7.1)	0.600
Developmental delays	38 (69.01)	6 (85.7)	11 (91.7)	14 (63.6)	7 (50.0)	0.094
Congenital malformations	31 (56.4)	4 (57.1)	10 (83.3)	12 (54.6)	5 (35.7)	0.115
Dysmorphic facies	42 (76.4)	6 (85.7)	11 (91.7)	16 (72.7)	9 (64.3)	0.406
Cardiovascular diagnoses	14 (25.5)	2 (28.6)	6 (50.0)	4 (18.2)	2 (14.3)	0.164
Renal concerns	16 (29.1)	2 (28.6)	6 (50.0)	7 (31.8)	1 (7.1)	0.100
Metabolic/endocrine concerns	10 (18.2)	2 (28.6)	3 (25.0)	3 (13.6)	2 (14.3)	0.722
Vision, hearing, or smell abnormalities	26 (47.3)	4 (57.1)	8 (66.7)	10 (45.5)	4 (28.6)	0.280
Behavioral health concerns	8 (14.6)	1 (14.3)	3 (25.0)	3 (13.6)	1 (7.1)	0.696
Autism spectrum disorder	19 (34.6)	2 (28.6)	6 (50.0)	7 (31.8)	4 (28.6)	0.685
ADHD	4 (7.3)	1 (14.3)	3 (25.0)	0 (0.0)	0 (0.0)	0.018
Family history of severe obesity	21 (38.2)	4 (57.1)	4 (33.3)	9 (40.9)	4 (28.6)	0.623
Parent or patient request	29 (52.7)	4 (57.1)	7 (58.3)	10 (45.5)	8 (57.1)	0.874
Just a feeling something isn't “right”	27 (49.1)	6 (85.7)	9 (75.0)	7 (31.8)	5 (35.7)	0.015
Other (please fill in)	3 (5.5)	1 (14.3)	0 (0.0)	0 (0.0)	2 (14.3)	0.103

	Mean ± SD	Mean ± SD	Mean ± SD	Mean ± SD	Mean ± SD
Total number of characteristics (range: 0–20)^b	7.90 ± 3.92	9.0 ± 4.83	10.30 ± 4.92^c	7.30 ± 2.99	6.20 ± 2.86^c	0.034

Indicates that the Fisher's exact test was used to test the association between YOE group and specific patient characteristics.

Indicates that the one-way ANOVA was used to compare the YOE group with the mean number of patient characteristics identified.

Tukey's post hoc test indicated a significant difference between these two groups.

ADHD, attention-deficit/hyperactivity disorder; SD, standard deviation.

Table 2 provides the frequencies of patient characteristics which prompted consideration of testing. There was a significant association between YOE groups and selection of the specific patient characteristics of attention-deficit/hyperactivity disorder (ADHD) (p = 0.02), and “just feeling something isn't right” (p = 0.02); both characteristics were more likely to be identified by those in the groups with fewer YOE. The average number of patient characteristics that prompted consideration of genetic screening varied significantly by YOE (one-way ANOVA, p = 0.03); respondents with 6–10 YOE indicated more patient characteristics than respondents with >20 YOE (mean 10.3 vs. mean 6.2).

Benefits and Drawbacks of Testing

The primary benefit of testing reported by participants (42%) was the health information obtained for patients/families. The reported primary drawback was the high number of indeterminate tests [i.e., variants of uncertain significance (VUS), 49%]. Only 8% of participants reported no drawbacks to testing. The following themes emerged on the benefits and drawbacks of testing; what to do, time and workload, insurance coverage and financial costs, impact of testing on the family, and physiology of obesity.

What to do

Providers reported challenges when test results were uncertain, that is, VUS. Providers were often unsure of how a VUS result would impact or guide treatment. The most common reason given was that it would not change patient management (15%). A participant noted, “We can name the variant, but do not currently have targeted treatments for this.” Others reported difficulty in knowing how to communicate to families the meaning of test results (8%).

Time and workload

Of the providers who reported testing (n = 44), 25% stated the process of tracking patient tests and results increased their workload. They described lacking sufficient skills and time for counseling patients and families on test results. Among providers who initiated testing, 34% created personal files to track patient tests and results, 32% reported no system, and 17% had access to a genetic counselor or nursing staff to help with workload.

Insurance coverage and financial costs

Participants had concerns about the cost of testing that may be incurred by patients and if it would be covered by insurance in the future, should the sponsored testing program by Rhythm be discontinued. One participant noted, “It (the genetic test) is rarely covered by insurance and doesn't change management.”

Impact of testing on the family

Participants reported testing would decrease the shame, blame, and guilt caregivers feel when their child has obesity, regardless of what the results were. A participant responded, “Perhaps (we) uncover a rare disorder that could benefit from treatment, but more often (we) just give family more information, sometimes take blame off of them and help family understand the chronic life-long nature of this disease.” Providers stated that a drawback of testing was that it would give false hope to families that there would be a genetic cause. In addition, they were concerned that inconclusive results would produce confusion and anxiety for families.

Physiology of obesity

Participants reported a benefit of testing was an increased understanding of the physiology of obesity and may uncover other causes of obesity and comorbid conditions in addition to rare syndromes. They were hopeful that the knowledge acquired in testing would lead to the development of other treatments. A participant stated “Just because we don't find a genetic cause doesn't mean there isn't one. It may just not be a genetic cause that comes up in the standard panels.”

Improving Communication With Patients

When asked what would facilitate discussions with patients and families when communicating results, 42% indicated more training, education, and guidance on how to interpret findings, in particular VUS, while 18% did not know or were unsure. They wanted more evidence to support testing and guidelines on when and whom to test. Participants suggested clinical guidelines and workflow algorithms would be helpful. Participants reported the need for patient and family education materials (i.e., handouts, websites) (70%). These materials should help explain the rationale for testing, how to understand the results, and treatment options. Respondents (24%) stated that having access to a genetic counselor would help facilitate communication with patients and families.

Ethics of Testing

Participants were asked to describe ethical concerns, which might impact their decision to test for rare disorders of obesity. Close to half (49%) had no ethical concerns about testing. Providers were concerned that it was unethical not to test if one was available, while others questioned the ethics of using a test provided by a for-profit pharmaceutical company. Participants were unclear about how the company handled test results, how data might be used without a patient's permission, and who might have access to these data in the future.

Participants were concerned that testing for obesity might increase discrimination, weight bias, and stigma for patients. Providers feared that for those who had “positive” results, this might impact their future insurance coverage. One participant stated, “My worry is that insurance companies will use a positive genetic test as a reason to increase insurance rates or deny coverage; I think that for certain genetic/inherited conditions, some people think that people should not have children and pass along those genes, and I wouldn't want there to be a cultural shift towards the way of thinking of obesity.”

Discussion

We obtained responses from 55 PWM providers on their experiences and perspectives of genetic testing for rare disorders of obesity. Most reported ordering genetic testing for their patients if indicated. We also obtained information to better understand circumstances surrounding testing, identified benefits, drawbacks, and ethics of testing, and gaps in provider knowledge. Providers cited several different patient characteristics which prompted testing, and this varied by provider YOE. Clinical decision-making involves both the “art” and science of medicine. The decision to obtain genetic testing is influenced by patient characteristics, provider awareness of patient risks, and the resources to conduct testing. Genetic testing does not replace usual management but is an additional tool for PWM.

The primary drawback of genetic testing was provider uncertainty of what to do with VUS results, their clinical meaning, and impact on current or future treatment. Published studies have reported 31%–88% of reported variants as VUS in individuals with obesity.^9,13,16 While these may reflect the expected prevalence in this population, providers noted it to be a challenge to explain such results to patients and families as no easily accessible reference database or studies are available for guidance. Pediatric and adult providers performing genetic testing for other chronic conditions and not specializing in genetics have reported difficulties in understanding, interpreting, and communicating findings from genetic testing to patients.^17–24

These challenges have been attributed to a gap in their medical education. Enhanced medical and continuing education in genetics/genomics and research into provider attitudes on the genetics of obesity and value of genetic testing are steps to consider. Doing this work collaboratively among providers of PWM across institutions could help reduce workload, establish consistency in practice, and accelerate adoption of testing.

Our findings suggest that a potential benefit of genetic testing may be reduction of shame, blame, and guilt for caregivers of children with obesity. While not identified in our survey, emerging targeted therapies are another future benefit of genetic testing. Reported drawbacks to testing include false hope and increasing confusion and anxiety for families when results are inconclusive. Researchers have previously reported that primary care providers (PCPs) believed telling patients that they have a genetic risk for chronic disease would cause excessive stress.¹⁹ In a recent study of caregivers, whose child received genetic testing for rare causes of obesity, caregivers reported motivation to change health behaviors or continue their current behaviors regardless of whether the test results showed a genetic cause for obesity.²⁵ Patient and family codesigned research is needed to uncover the impact genetic knowledge has on patient and family wellbeing.

Participants in our study reported an increased workload with genetic testing, including time for communication of results, further education, and lack of clinical support to create and maintain a database of patient tests/results. A minority of providers had support from nursing or genetic counselors. Previously, PCPs reported the need for a process to order and understand genetic tests and manage patients with positive test results.¹⁹ Respondents in our study overwhelmingly wanted educational resources on how to talk with patients and families about genetics and genetic testing. This highlights a need for the development of clinical tools to improve workflows related to implementing genetic testing into practice.

Some participants reported ethical concerns with testing. These included how results are handled by the testing company; using data without patient's permission; data security; and increased stigma and discrimination, specifically impacting future insurance coverage. The Genetics Non-Discrimination Act of 2008 (GINA)²⁶ prohibits discrimination on the basis of genetic information with respect to health insurance and employment, although it does not provide protection for life, disability, or long-term care insurance or individuals seeking to join the military. Providers implementing genetic testing may need to increase knowledge of GINA and identify resources to address ethical, legal, and social implications of genetic testing.²⁷

Some participants in our study had concerns about how testing may increase weight stigma and general discrimination of their patients. Previous research has reported the collection of genetic information may increase the possibility of stigmatization of certain groups, particularly those of racial and ethnic minorities.^3,28,29 Currently, only one state in the United States (Michigan) has an antiweight discrimination law.³⁰ Research should explore associations with genetic testing and instances of stigma and discrimination. Research should include the views and concerns of patients with obesity and their families related to testing for genetic predisposition to obesity.

Strengths and Limitations

This is the first study reporting on clinician routines and perceptions of genetic testing when managing youth with obesity. Strengths of this work include the generation of data from providers that care for pediatric patients with obesity across the United States. The data reported may lead to the development of strategies and resources that could aid clinicians in the process of genetic testing for youth with obesity.

A limitation of this study was the inability to track response rate, therefore, our sampling used methods to overcome the lack of a database of providers of PWM care. We were unable to track how many recipients and respondents we had due to snowball sampling; therefore, an accurate denominator could not be calculated. To preserve anonymity, we collected age and provider YOE as categorical variables; our groups for these variables may have influenced results. Finally, our sample size was small and obtained using purposive sampling, therefore, results may not be generalizable to all providers of PWM.

Conclusions

This is the first study to identify the perceptions and practices of testing for rare genetic disorders of obesity in providers of PWM. Most respondents reported genetic testing as an option for patient management. Provider training in genetics and genomics, as well as research into provider and family attitudes on the genetics of obesity and value of genetic testing are next steps to consider. These steps will facilitate processes aimed at developing and implementing effective clinical decision algorithms and shared decision-making related to genetic testing in PWM.

Impact Statement

Genomic medicine allows personalized health care with targeted management. PWM providers are increasingly using genetic testing to identify rare disorders of obesity, but desire additional resources. Our results can be used to develop strategies to prepare these providers to integrate genomic medicine in pediatric obesity care.

Footnotes

Acknowledgments

The authors acknowledge Lenore R. Wilkas MLS research librarian from UW-Milwaukee College of Nursing for her help with the literature search. This study was made possible by the availability of sponsored genetic testing by Rhythm^® Pharmaceuticals that has allowed free access to genetic testing for rare causes of obesity.

Authors' Contributions

K.J.R.: conceptualization, methodology, formal analysis, validation, investigation, writing original draft, and project administration, E.C.: methodology, formal analysis, and writing—review and editing, A.J.A.: conceptualization, methodology, and writing—review and editing, V.V.T.: methodology and writing—review and editing, C.C.C.: formal analysis and writing—review and editing, and H.J.B.: conceptualization, methodology, and writing—review and editing.

Funding Information

No funding was received for this article.

Author Disclosure Statement

No competing financial interests exist.

Supplementary Material

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