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  1. Eur J Hum Genet. 2009 Feb; 17(2): 147–149. Published online 2008 Oct 22. doi: 10.1038/ejhg.2008.198 PMCID: PMC2986051 On Jim Watson's APOE status: genetic information is hard to hide Dale R Nyholt,1,* Chang-En Yu,2 and Peter M Visscher1 Author information ► Copyright and License information ► This article has been cited by other articles in PMC. The recent publication and release to public databases of Dr James Watson's sequenced genome,1 with the exception of all gene information about apolipoprotein E (ApoE), provides a pertinent example of the challenges concerning privacy and the complexities of informed consent in the era of personalized genomics.2 Dr Watson requested that his ApoE gene (APOE) information be redacted, citing concerns about the association that has been shown with late onset Alzheimer's disease (LOAD), which is currently incurable and claimed one of his grandmothers.3 In this letter, without any ‘analysis' of Dr Watson's genome, and thus respecting Dr Watson's wishes for APOE risk status anonymity, we highlight the challenges concerning the privacy and the complexities of informed consent by pointing out that the deletion of the APOE gene information only may not prevent accurate prediction of Dr Watson's risk for LOAD conveyed by APOE risk alleles. Specifically, linkage disequilibrium (LD) between one or multiple polymorphisms and APOE can be used to predict APOE status using advanced computational tools. Therefore, simply blanking out genotypes at known risk factors is generally not sufficient if the aim is to hide genetic information at these loci. The major APOE risk for LOAD is generally assumed to come from the ɛ2/ɛ3/ɛ4 haplotype system, with the ɛ4 allele increasing risk for the disorder and the ɛ2 allele being protective.4 The ɛ2/ɛ3/ɛ4 haplotype system is defined by two nonsynonymous single nucleotide polymorphisms (SNPs) in APOE exon 4. One is a C/T SNP (rs429358) that encodes either arginine (C) or cysteine (T) in the ApoE at amino acid 112. The second site defining this haplotype system is a C/T SNP (rs7412), which again encodes arginine (C) or cysteine (T) at ApoE amino acid 158. The allelic compositions of the commonly investigated rs429358-rs7412 haplotypes are T-T for ɛ2, T-C for ɛ3, and C-C for ɛ4. The effects of these coding variants on ApoE function are well defined.5 A recent meta-analysis of LOAD risk in Caucasians (clinic/autopsy cohorts) indicated odds ratios (OR) of 15.6 (95% CI, 10.9–22.5) and 4.3 (95% CI, 3.3–5.5) for APOE ɛ4 homozygotes and ɛ4/ɛ3heterozygotes respectively, compared to ɛ3 homozygotes.6 The meta-analytic odds ratios in population-based Caucasian samples were 11.8 (95% CI, 7.0–19.8) and 2.8 (95% CI, 2.3–3.5), respectively.6 In a large Rotterdam (Netherlands), population-based prospective study of people aged 55 years or above, it was estimated that 17% of the overall risk of AD could be attributed to the ɛ4 allele, with 3% (95% CI, 0–6%) of cases attributed to the ɛ4/ɛ4 genotype, and 14% (95% CI, 7–21%) to the ɛ4/ɛ3 genotype.7 A recent investigation of LD for 50 SNPs in and surrounding APOE in 550 Caucasians identified multiple SNPs in the TOMM40 gene ∼15 kb upstream of APOE, and at least one SNP in the other surrounding genes LU, PVRL2, APOC1, APOC4 and CLPTM1 were associated with LOAD risk.8 In particular, the C allele of SNP rs157581 in TOMM40 is in strong LD (r2>0.6) with the C allele of rs429358 in APOE, which defines the ɛ4 allele. For an additive (allelic) logit model, the OR for the presence of ɛ4 versus the status of LOAD was estimated to be 4.1, whereas the OR for LOAD status using the alleles of rs157581 was 2.9.8Furthermore, using data sets such as those of Yu et al8 and SNPs identified in the surrounding regions of APOE in Dr Watson's sequence, haplotype phasing software could be utilized to easily and accurately predict Dr Watson's APOE risk haplotype status. In addition, even if genotypes for non-APOE SNPs conveying LOAD risk are not listed in Dr Watson's sequence (ie, because of low sequence coverage), as in the case of TOMM40 SNP rs157581, it would be straightforward to predict Dr Watson's APOE risk status by exclusively using publicly available data, such as HapMap data. Specifically, although the LOAD high-risk APOE SNPs rs429358 and rs7412 and TOMM40 SNP rs157581 are not in the HapMap, a recent genome-wide association screen using 502 627 SNPs performed in 1086 histopathologically verified LOAD cases (n=664) and controls (n=442), identified HapMap SNP rs4420638, located in the APOC1 gene 14 kb downstream of the APOE ɛ4 allele, which has a powerful association with LOAD.9 Indeed, the association between LOAD and the G allele of rs4420638 (P=1 × 10−39) is similar to the association with the APOE ɛ4 allele (rs429358 C allele) itself (P=1 × 10−44), with additive allelic ORs of approximately 4 and 5, respectively.9, 10 Coon et al9 report strong LD between rs4420638 and rs429358 at D′=0.86, which implies an r2 of approximately 0.60 based on Caucasian allele frequency estimates for these SNPs listed in dbSNP. We note that Dr Watson received genetic counseling and after being made aware of the privacy risks associated with public data broadcast, Dr Watson decided to share his personal genome by releasing it into a publicly accessible scientific database (for full details concerning Dr Watson and Protection of human subjects, Returning research results to research participants, and Data release and data flow, see Box 1 of Wheeler et al1). Nevertheless, during the preparation of this Letter, we contacted Dr Watson and colleagues in December 2007 and February 2008 informing them of the possibility of inferring his risk for LOAD conveyed by APOE risk alleles using surrounding SNP data. As a consequence, the online James Watson Genome Browser (JWGB) has nominally removed all data from the 2-Mb region surrounding APOE. To demonstrate our point that genetic information is hard to hide, without contravening Dr Watson's wishes for APOE risk status anonymity (see Box 1 of Wheeler et al1), we utilized SNP genotypes identified in Dr J Craig Venter's genome sequence.11 Furthermore, Dr Venter's sequence data reports that he is heterozygote for both the LOAD high-risk APOE SNP rs429358 (T/C) and APOC1 SNP rs4420638 (A/G). Briefly, genotype imputation was performed using the MACH (version 1.0.16) computer program,12 HapMap (CEU)-phased haplotype data (encompassing 144 SNPs) and Dr Venter's genotypes listed for the 200-kb region surrounding rs4420638 (encompassing all 144 HapMap SNPs). Following the two-step approach outlined in the MACH online tutorial and after excluding Dr Venter's genotype data for rs4420638 and all APOE SNPs, we were able to correctly impute Dr Venter's rs4420638 genotype as A/G. The posterior probabilities for Dr Venter's rs4420638 genotype being A/A, A/G or G/G were estimated to be 0.008, 0.992 and 0.000, respectively. The high accuracy of Dr Venter's imputed rs4420638 genotype exemplifies the utility of imputing APOE genetic risk for LOAD. Finally, although the deletion of 2 Mb is likely excessive for the surrounding APOE region (based on reported LD), as more detailed characterization of the human genome comes to light, it will become even more necessary to redact substantial regions surrounding identified genetic risk variants to avoid the indirect, though accurate, estimation of genetic risk such as those we detail above. For example, in a recent study, using gene expression profiling of Epstein–Barr virus-transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium, Stranger et al13 reported many instances of the most significant SNP associated with gene expression being located often 100 s of kb and up to 1 Mb outside of the gene transcript, with additional, less significant SNPs, although still useful in estimating risk, being located even further from the gene. Moreover, the potential for indirect estimation of risk will further increase as additional and more detailed genome-wide association studies are performed (which identify new risk loci) and individual human genomes are sequenced. In summary, hiding genetic information in an otherwise fully disclosed genome sequence is not straightforward because of the availability of genomic data in the public domain that can be used to predict the missing data. We believe the potential for such indirect estimation of genetic risk has considerable relevance to concerns about privacy, confidentiality, discriminatory and defamatory use of genetic data, and the complexities of informed consent for both research participants and their close genetic relatives in the era of personalized genomics. Acknowledgments This study was supported by Australian NHMRC Grants 389892, 339462 and 442915 and Australian Research Council Grant DP0770096. Footnotes Conflict of interest None declared. Web Resources The URL for data presented here are as follows: James Watson Genome Browser (JWGB), http://jimwatsonsequence.cshl.edu/cgi-perl/gbrowse/jwsequence/ James Watson Genome Browser (JWGB); local copy installation download, ftp://jimwatsonsequence.cshl.edu/jimwatsonsequence/gbrowse/ Dr J Craig Venter's genome sequence, http://huref.jcvi.org/ MACH (version 1.0.16) computer program, http://www.sph.umich.edu/csg/abecasis/MACH HapMap (CEU) phased haplotype data (encompassing 144 SNPs), http://www.hapmap.org/cgi-perl/gbrowse/hapmap_B35/ Dr Venter's genotypes (downloaded on June 19, 2008), ftp://ftp.jcvi.org/pub/data/huref/HuRef.InternalHuRef-NCBI.gff MACH online tutorial, http://www.sph.umich.edu/csg/abecasis/MACH/tour/imputation.html References Wheeler DA, Srinivasan M, Egholm M, et al. The complete genome of an individual by massively parallel DNA sequencing. Nature. 2008;452:872–876. [PubMed] McGuire AL, Caulfield T, Cho MK. Research ethics and the challenge of whole-genome sequencing. Nat Rev Genet. 2008;9:152–156. [PMC free article] [PubMed] Check E. James Watson's genome sequenced – discoverer of the double helix blazes trail for personal genomics Nature News 2008. doi:10.1038/news070528-10 :http://www.nature.com/news/2007/070528/full/news070528-10.html [Cross Ref] Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA. 1997;278:1349–1356. [PubMed] Raber J, Huang Y, Ashford JW. ApoE genotype accounts for the vast majority of AD risk and AD pathology. Neurobiol Aging. 2004;25:641–650. [PubMed] Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet. 2007;39:17–23. [PubMed] Slooter AJ, Cruts M, Kalmjin S, et al. Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: the Rotterdam Study. Ann Neurol. 1998;55:964–968. [PubMed] Yu CE, Seltman H, Peskind ER, et al. Comprehensive analysis of APOE and selected proximate markers for late-onset Alzheimer's disease: patterns of linkage disequilibrium and disease/marker association. Genomics. 2007;89:655–665. [PMC free article] [PubMed] Coon KD, Myers AJ, Craig DW, et al. A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. J Clin Psychiatry. 2007;68:613–618. [PubMed] Reiman EM. In this issue: entering the era of high-density genome-wide association studies. J Clin Psychiatry. 2007;68:611–612. [PubMed] Levy S, Sutton G, Ng PC, et al. The diploid genome sequence of an individual human. PLoS Biol. 2007;5:e254. [PMC free article] [PubMed] Li Y, Abecasis GR. Mach 1.0: rapid haplotype reconstruction and missing genotype inference. Am J Hum Genet. 2006;S79:2290. Stranger BE, Nica AC, Forrest MS, et al. Population genomics of human gene expression. Nat Genet. 2007;39:1217–1224. [PMC free article] [PubMed] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2986051/ Articles from European Journal of Human Genetics are provided here courtesy of Nature Publishing Group
  2. New Gene Tests Pose a Threat to Insurers By GINA KOLATA MAY 12, 2017 https://www.nytimes.com/2017/05/12/health/new-gene-tests-pose-a-threat-to-insurers.html?smid=tw-nythealth&smtyp=cur&_r=0 Photo Pat Reilly, 77, at home in Ann Arbor, Mich., last week. Ms. Reilly found that she had inherited an ApoE4 gene that increases the risk of developing Alzheimer’s disease, and bought a long-term care policy in response.CreditLaura McDermott for The New York Times Pat Reilly had good reason to worry about Alzheimer’s disease: Her mother had it, and she saw firsthand the havoc it could wreak on a family, much of it financial. So Ms. Reilly, 77, a retired social worker in Ann Arbor, Mich., applied for a long-term care insurance policy. Wary of enrolling people at risk for dementia, the insurance company tested her memory three times before issuing the policy. But Ms. Reilly knew something the insurer did not: She has inherited the ApoE4 gene, which increases the lifetime risk of developing Alzheimer’s. “I decided I’d best get long-term care insurance,” she said. An estimated 5.5 million people in the United States have Alzheimer’s disease, and these patients constitute half of all nursing home residents. Yet very few people in the United States have been tested for the ApoE4 gene. But last month, with the approval of the Food and Drug Administration, the gene testing company 23andMe began offering tests that reveal whether people have the variant, as well as assessing their risks for developing such conditions as Parkinson’s and celiac disease. Other genetics companies are planning to offer similar tests, and soon millions of people will have a better idea what their medical futures might be. Recent research has found that many, like Ms. Reilly, are likely to begin preparing for the worst. But for companies selling long-term care insurance, these tests could be a disaster, sending risky patients in search of policies even as those with fewer risks shy away, damaging an already fragile business. “There is a question about whether the industry is in a death spiral anyway,” said Robert Hunter, director of insurance at the Consumer Federation of America. “This could make it worse.” The tests are simple: All people have to do is send away a saliva sample and pay $199. Their disease risks, if they say they want to know them, will be delivered with a report on ancestry and on how their genes influence such traits as flushing when they drink alcohol or having straight hair. The company will not reveal how many people have received disease-risk data, but it says that in Britain and Canada, where it has offered such testing for several years, about three-quarters of their customers have asked for it. 23andMe has sold its genetic services to more than two million people worldwide since 2007. The issue for now is with long-term care insurance, not employment and not — at least so far — health insurance. Under the Genetic Information Nondiscrimination Act, companies cannot ask employees to take gene tests and cannot use any such results in employment decisions; insurers are not permitted to require gene tests or to use the results in coverage decisions. But legislation proposed in the House would exempt corporate “wellness” programs from some of these requirements. And the American Health Care Act, passed by the House, would permit states to waive some insurance safeguards regarding pre-existing conditions. At the moment, companies selling long-term care insurance — unlike medical insurers — are permitted to ask about health status and take future health into consideration when deciding whom to insure and how much to charge. The 23andMe test results will not appear in people’s medical records, and the company promises not to disclose identifiable findings to third parties. It is up to the customers to reveal them — and the fear for insurers is that many will not. Two-thirds of nursing home residents are on Medicaid, and the remaining private insurers are already struggling. In the early 2000s, more than 100 firms offered long-term care insurance, according to the Treasury Department. By the end of 2015, only 12 firms offered it, and new enrollees fell from 171,000 to 104,000. The insurers charged too little for these policies, experts say; policyholders have turned out to be much sicker than anticipated. To pay for an unanticipated increase in policyholders who develop Alzheimer’s, insurers would have to raise prices, said Don Taylor, a professor of public policy at Duke University who has studied the issue. Increasing numbers of people at low risk might decide the insurance was not worth the rising price. Even many at high risk would eventually find the policies unaffordable. It is the definition of an insurance death spiral. If that happens, said Mark Rothstein, the director of the bioethics institute at the University of Louisville’s medical school, even more people with Alzheimer’s will end up on Medicaid, with the federal government paying for their nursing home care. Someone must pay, he said. The only question is whether it will be taxpayers or policyholders. “How do you want to spread the risk?” Mr. Rothstein asked. For 23andMe, the new tests are simply a way to help people learn about their makeup. “People clearly want information about themselves,” said Anne Wojcicki, the chief executive at 23andMe. “There is a demand.” Yet even if just a minority of 23andMe customers decided to game the current insurance system, “it’s enough to perturb the market,” said Dr. Robert Cook-Deegan, a professor at the school for the future of innovation in society at Arizona State University, who has studied the issue. Research by Dr. Robert C. Green, a geneticist at Harvard University, indicates that this is exactly what is likely to happen. Drawing on data from his clinical trials involving more than 1,000 people, Dr. Green has found that people who learn they have the ApoE4 gene fare just as well if they get the results without counseling. But he also found that those who learned they had the gene variant — Ms. Reilly was one of them — were nearly six times more likely to buy long-term care insurance than those who did not. The ApoE4 gene variant is present in about a quarter of the population. Many thought there was no need to tell the insurer why they suddenly wanted a policy. “All the insurance companies are concerned about this,” said Dr. Green, who has been discussing the problem with industry executives. Major insurers declined to comment. A trade group, American Council of Life Insurers, issued an email statement by Mariana Gomez-Vock, the group’s senior counsel. “Though it is difficult to speculate on the potential impact of the latest 23andMe offering, any situation that has the ability to significantly increase adverse selection could impact the availability and affordability of products over time,” she wrote. “We need to be on the same page with the applicant, where both sides share the same information,” she added. But will that happen? “I don’t see a good outcome here,” Mr. Taylor said. Correction: May 16, 2017 An earlier version of this article misstated the name of the legislation that prevents companies and insurers from using gene tests to make employment or coverage decisions. It is the Genetic Information Nondiscrimination Act, not the Genetic Information Nondiscrimination Privacy Act.
  3. NY Times has a report on 23andme FDA approved test for late onset Alzheimer's disease and impact on long term care heath insurance. However, the determination of APOE4 status can be determined through additional markers on Chromosome 19.
  4. http://www.renseradio.com/listenlive.htm
  5. Tonight at 10 PM - Personal DNA Testing THURSDAY Dr. Henry L. Niman, PhD
  6. FDA allows marketing of first direct-to-consumer tests that provide genetic risk information for certain conditions SHARE TWEET LINKEDIN PIN IT EMAIL PRINT For Immediate Release April 6, 2017 Release Español The U.S. Food and Drug Administration today allowed marketing of 23andMe Personal Genome Service Genetic Health Risk (GHR) tests for 10 diseases or conditions. These are the first direct-to-consumer (DTC) tests authorized by the FDA that provide information on an individual’s genetic predisposition to certain medical diseases or conditions, which may help to make decisions about lifestyle choices or to inform discussions with a health care professional. “Consumers can now have direct access to certain genetic risk information,” said Jeffrey Shuren, M.D., director of the FDA’s Center for Devices and Radiological Health. “But it is important that people understand that genetic risk is just one piece of the bigger puzzle, it does not mean they will or won’t ultimately develop a disease.” The GHR tests are intended to provide genetic risk information to consumers, but the tests cannot determine a person’s overall risk of developing a disease or condition. In addition to the presence of certain genetic variants, there are many factors that contribute to the development of a health condition, including environmental and lifestyle factors. The 23andMe GHR tests work by isolating DNA from a saliva sample, which is then tested for more than 500,000 genetic variants. The presence or absence of some of these variants is associated with an increased risk for developing any one of the following 10 diseases or conditions: Parkinson’s disease, a nervous system disorder impacting movement; Late-onset Alzheimer’s disease, a progressive brain disorder that destroys memory and thinking skills; Celiac disease, a disorder resulting in the inability to digest gluten; Alpha-1 antitrypsin deficiency, a disorder that raises the risk of lung and liver disease; Early-onset primary dystonia, a movement disorder involving involuntary muscle contractions and other uncontrolled movements; Factor XI deficiency, a blood clotting disorder; Gaucher disease type 1, an organ and tissue disorder; Glucose-6-Phosphate Dehydrogenase deficiency, also known as G6PD, a red blood cell condition; Hereditary hemochromatosis, an iron overload disorder; and Hereditary thrombophilia, a blood clot disorder. The FDA reviewed data for the 23andMe GHR tests through the de novo premarket review pathway, a regulatory pathway for novel, low-to-moderate-risk devices that are not substantially equivalent to an already legally marketed device. Along with this authorization, the FDA is establishing criteria, called special controls, which clarify the agency’s expectations in assuring the tests’ accuracy, reliability and clinical relevance. These special controls, when met along with general controls, provide reasonable assurance of safety and effectiveness for these and similar GHR tests. In addition, the FDA intends to exempt additional 23andMe GHR tests from the FDA’s premarket review, and GHR tests from other makers may be exempt after submitting their first premarket notification. A proposed exemption of this kind would allow other, similar tests to enter the market as quickly as possible and in the least burdensome way, after a one-time FDA review. “The special controls describe the testing that 23andMe conducted to demonstrate the performance of these tests and clarify agency expectations for developers of other GHRs,” said Dr. Shuren. “By establishing special controls and eventually, a premarket review exemption, the FDA can provide a streamlined, flexible approach for tests using similar technologies to enter the market while the agency continues to help ensure that they provide accurate and reproducible results.” Excluded from today’s marketing authorization and any future, related exemption are GHR tests that function as diagnostic tests. Diagnostic tests are often used as the sole basis for major treatment decisions, such as a genetic test for BRCA, for which a positive result may lead to prophylactic (preventative) surgical removal of breasts or ovaries. Authorization of the 23andMe GHR tests was supported by data from peer-reviewed, scientific literature that demonstrated a link between specific genetic variants and each of the 10 health conditions. The published data originated from studies that compared genetic variants present in people with a specific condition to those without that condition. The FDA also reviewed studies, which demonstrated that 23andMe GHR tests correctly and consistently identified variants associated with the 10 indicated conditions or diseases from a saliva sample. The FDA requires the results of all DTC tests used for medical purposes be communicated in a way that consumers can understand and use. A user study showed that the 23andMe GHR tests’ instructions and reports were easy to follow and understand. The study indicated that people using the tests understood more than 90 percent of the information presented in the reports. Risks associated with use of the 23andMe GHR tests include false positive findings, which can occur when a person receives a result indicating incorrectly that he or she has a certain genetic variant, and false negative findings that can occur when a user receives a result indicating incorrectly that he or she does not have a certain genetic variant. Results obtained from the tests should not be used for diagnosis or to inform treatment decisions. Users should consult a health care professional with questions or concerns about results. The FDA granted market authorization of the Personal Genome Service GHR tests to 23andMe, Inc. The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nation’s food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products. https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm551185.htm
  7. I have recently begun to look at personal DNA testing. Initial observations are for two of the more popular home tests (23andme and ancestry.com). Both services include raw data on over 500,000 snps, which include many predictive markers for a variety of medical conditions, including cancer. Recently, 10 of the 23andme tests have received FDA approval.
  8. Idaho Payette County in the State of Idaho, on or after December 19, 2014 and before May 19, 2015 as well as on or after April 11, 2017 are ineligible for export.* https://www.fsis.usda.gov/wps/portal/fsis/topics/international-affairs/exporting-products/export-library-requirements-by-country/Nicaragua
  9. Idaho Payette County in the State of Idaho, on or after December 19, 2014 and before May 19, 2015 as well as on or after April 13, 2017 are ineligible for export.* https://www.fsis.usda.gov/wps/portal/fsis/topics/international-affairs/exporting-products/export-library-requirements-by-country/Honduras
  10. Idaho - Poultry meat and meat products loaded on board vessel on or before April 10, 2017.* https://www.fsis.usda.gov/wps/portal/fsis/topics/international-affairs/exporting-products/export-library-requirements-by-country/taiwan
  11. Poultry slaughtered on or after March 15, 2017, which originated from or passed through or is slaughtered/processed within the zone shown on the attached map is ineligible. Within the zone, poultry slaughtered and processed before March 15 , 2017 is eligible.* https://www.fsis.usda.gov/wps/portal/fsis/topics/international-affairs/exporting-products/export-library-requirements-by-country/Japan
  12. References Meaney-Delman D, Hills SL, Williams C, et al. Zika virus infection among U.S. pregnant travelers, August 2015–February 2016. MMWR Morb Mortal Wkly Rep 2016;65:211–4. CrossRef PubMed Simeone RM, Shapiro-Mendoza CK, Meaney-Delman D, et al. ; Zika and Pregnancy Working Group. Possible Zika virus infection among pregnant women—United States and Territories, May 2016. MMWR Morb Mortal Wkly Rep 2016;65:514–9. CrossRef PubMed Honein MA, Dawson AL, Petersen EE, et al. ; US Zika Pregnancy Registry Collaboration. Birth defects among fetuses and infants of US women with evidence of possible Zika virus infection during pregnancy. JAMA 2017;317:59–68. CrossRef PubMed Cragan JD, Mai CT, Petersen EE, et al. Baseline prevalence of birth defects associated with congenital Zika virus infection—Massachusetts, North Carolina, and Atlanta, Georgia, 2013–2014. MMWR Morb Mortal Wkly Rep 2017;66:219–22. CrossRef PubMed Rabe IB, Staples JE, Villanueva J, et al. ; MTS. Interim guidance for interpretation of Zika virus antibody test results. MMWR Morb Mortal Wkly Rep 2016;65:543–6. CrossRef PubMed Council of State and Territorial Epidemiologists. Zika virus disease and Zika virus infection 2016 case definition. CSTE position statement 16-IC-01. Atlanta, GA: Council of State and Territorial Epidemiologists; 2016. https://wwwn.cdc.gov/nndss/conditions/zika/case-definition/2016/06/ Moore CA, Staples JE, Dobyns WB, et al. Characterizing the pattern of anomalies in congenital Zika syndrome for pediatric clinicians. JAMA Pediatr 2017;171:288–95. CrossRef PubMed Russell K, Oliver SE, Lewis L, et al. ; Contributors. Update: interim guidance for the evaluation and management of infants with possible congenital Zika virus infection—United States, August 2016. MMWR Morb Mortal Wkly Rep 2016;65:870–8. CrossRef PubMed van der Linden V, Pessoa A, Dobyns W, et al. Description of 13 infants born during October 2015–January 2016 with congenital Zika virus infection without microcephaly at Birth—Brazil. MMWR Morb Mortal Wkly Rep 2016;65:1343–8. CrossRef PubMed Alarcon A, Martinez-Biarge M, Cabañas F, Quero J, García-Alix A. A prognostic neonatal neuroimaging scale for symptomatic congenital cytomegalovirus infection. Neonatology 2016;110:277–85. CrossRef PubMed Bhatnagar J, Rabeneck DB, Martines RB, et al. Zika virus RNA replication and persistence in brain and placental tissue. Emerg Infect Dis 2017;23:405–14. CrossRef PubMed Oduyebo T, Igbinosa I, Petersen EE, et al. Update: interim guidance for health care providers caring for pregnant women with possible Zika virus exposure—United States, July 2016. MMWR Morb Mortal Wkly Rep 2016;65:739–44. CrossRef PubMed
  13. TABLE 2. Postnatal neuroimaging* and infant Zika virus testing results for 895 liveborn infants in the U.S. Zika Pregnancy Registry — 50 U.S. states and the District of Columbia, 2016 Testing No (%) liveborn infants With birth defects Without birth defects Total Total 45 850 895 Neuroimaging Any neuroimaging reported to USZPR 29 (64) 192 (23) 221 (25) Infant Zika virus testing Positive test result on an infant specimen†,§ 25 (56) 69 (8) 94 (11) Negative infant test results among infants with ≥1 infant specimen reported as tested 17 (38) 474 (56) 491 (55) No infant specimen test results reported to USZPR 3 (7) 307 (36) 310 (35) Abbreviations: IgM= immunoglobulin M; NAT=nucleic acid test; RT-PCR = reverse transcription–polymerase chain reaction; USZPR = U.S. Zika Pregnancy Registry. * Neuroimaging includes any cranial ultrasound, computed tomography, or magnetic resonance imaging test reported to the USZPR. † Positive infant tests included the presence of Zika virus RNA by a positive NAT (e.g., RT-PCR) and/or serological results of IgM positive/equivocal. § Infant specimens include serum, urine, blood, cerebrospinal fluid, cord serum, and cord blood.
  14. TABLE 1. Pregnancy outcomes* for 972 women with completed pregnancies† with laboratory evidence of possible recent Zika virus infection, by maternal symptom status and timing of symptom onset or exposure — U.S. Zika Pregnancy Registry, United States, December 2015–December 2016 Characteristic Brain abnormalities and/or microcephaly (No.) NTDs and early brain malformations, eye abnormalities, or consequences of CNS dysfunction without brain abnormalities or microcephaly (No.) Total with ≥1 birth defect (No.) Completed pregnancies (No.) Proportion affected by Zika virus–associated birth defects, % (95% CI§) Any laboratory evidence of possible recent Zika virus infection¶ Total 43 8 51 972 5 (4–7) Maternal symptom status Symptoms of Zika virus infection reported 18 3 21 348 6 (4–9) No symptoms of Zika virus infection reported 24 4 28 599 5 (3–7) Unknown 1 1 2 25 — Timing of symptoms or exposure** First trimester††,§§ 13 1 14 157 9 (5–14) Multiple trimesters including first 22 6 28 396 7 (5–10) Confirmed evidence of Zika virus infection¶¶ Total 18 6 24 250 10 (7–14) Maternal symptom status Symptoms of Zika virus infection reported 8 3 11 141 8 (4–13) No symptoms of Zika virus infection reported 10 2 12 102 12 (7–19) Unknown 1 0 1 7 — Timing of symptoms or exposure** First trimester††,§§ 8 1 9 60 15 (8–26) Multiple trimesters including first 8 4 12 58 21 (12–33) Abbreviations: CI = confidence interval; CNS = central nervous system; IgM= immunoglobulin M; NAT=nucleic acid test; NTD = neural tube defect; PRNT = plaque reduction neutralization test; RT-PCR = reverse transcription–polymerase chain reaction. * Outcomes for multiple gestation pregnancies are counted once. † Includes live births, spontaneous abortions, terminations, and stillbirths. § 95% CI for a binomial proportion using Wilson score interval. ¶ Includes maternal, placental, or fetal/infant laboratory evidence of possible recent Zika virus infection based on presence of Zika virus RNA by a positive NAT (e.g., RT-PCR) or similar test, serological evidence of a recent Zika virus infection, or serological evidence of a recent unspecified flavivirus infection. ** Estimates were not calculated for exposure in other trimesters because of small numbers. Pregnant women who did not have first trimester exposure might have had exposure in the periconceptional period only (8 weeks before conception or 6 weeks before and 2 weeks after the first day of the last menstrual period), second trimester, third trimester, both the second and third trimester; many women were missing information on trimester of exposure. †† First trimester is defined as last menstrual period +14 days to 13 weeks, 6 days (97 days). §§ First trimester exposure includes women with exposure limited to the first trimester and women with exposure limited to the first trimester and periconceptional period. ¶¶ Includes maternal, placental, or fetal/infant laboratory evidence of confirmed Zika virus infection based on presence of Zika virus RNA by a positive NAT (e.g., RT-PCR) or similar test or serological results of IgM positive/equivocal with Zika PRNT ≥10 and dengue PRNT <10.