Literature DB >> 28705149

f-treeGC: a questionnaire-based family tree-creation software for genetic counseling and genome cohort studies.

Tomoharu Tokutomi1,2, Akimune Fukushima3,4, Kayono Yamamoto1,2, Yasushi Bansho5, Tsuyoshi Hachiya6, Atsushi Shimizu6.   

Abstract

BACKGROUND: The Tohoku Medical Megabank project aims to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the areas affected by the Great East Japan Earthquake. We collected medical and genomic information for developing a biobank to be used for this healthcare system. We designed a questionnaire-based pedigree-creation software program named "f-treeGC," which enables even less experienced medical practitioners to accurately and rapidly collect family health history and create pedigree charts.
RESULTS: f-treeGC may be run on Adobe AIR. Pedigree charts are created in the following manner: 1) At system startup, the client is prompted to provide required information on the presence or absence of children; f-treeGC is capable of creating a pedigree up to three generations. 2) An interviewer fills out a multiple-choice questionnaire on genealogical information. 3) The information requested includes name, age, gender, general status, infertility status, pregnancy status, fetal status, and physical features or health conditions of individuals over three generations. In addition, information regarding the client and the proband, and birth order information, including multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included. 4) f-treeGC shows only marriages between first cousins via the overlay function. 5) f-treeGC automatically creates a pedigree chart, and the chart-creation process is visible for inspection on the screen in real time. 6) The genealogical data may be saved as a file in the original format. The created/modified date and time may be changed as required, and the file may be password-protected and/or saved in read-only format. To enable sorting or searching from the database, the file name automatically contains the terms typed into the entry fields, including physical features or health conditions, by default. 7) Alternatively, family histories are collected using a completed foldable interview paper sheet named "f-sheet", which is identical to the questionnaire in f-treeGC.
CONCLUSIONS: We developed a questionnaire-based family tree-creation software, named f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature. The present software simplifies the process of collecting family histories and pedigrees, and has a variety of uses, from genome cohort studies or primary care to genetic counseling.

Entities:  

Keywords:  Biobank; Family health history; Family tree; Genetic counseling; Genome cohort studies; Interview sheet; Pedigree; Primary care; Questionnaire; Software

Mesh:

Year:  2017        PMID: 28705149      PMCID: PMC5512935          DOI: 10.1186/s12881-017-0433-4

Source DB:  PubMed          Journal:  BMC Med Genet        ISSN: 1471-2350            Impact factor:   2.103


Background

Genealogical information is critical for accurate genetic diagnosis in clinical genetics. In 1995, the National Society of Genetic Counselors [1] introduced a standardized description method for presenting a family tree in genetic counseling, which was revised in 2008 to the current version [2]. Typically, pedigree charts are manually created via face-to-face personal interviews held on an individual basis. However, pedigree chart creation requires graphical skills and specialized knowledge of clinical genetics, and is thus a time- and labor-intensive process. A large amount of genetic data has been collected from numerous large-scale studies conducted in recent years, such as genome-cohort studies. The availability of accurate genealogical information is essential for performing comprehensive analysis of polymorphisms and associated diseases for use in genetic counseling, research, and diagnosis. Given the large amount of genetic information required and collected, it is currently not possible to create pedigree charts using the traditional method through interviews at a single recruiting event by an expert. The Tohoku Medical Megabank (TMM) project [3] aims to restore community medical services that were negatively affected by the Great East Japan Earthquake, and to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the disaster-stricken areas [4]. Specifically, we collected medical and genomic information, including family health history, for developing a biobank to be used in the planned healthcare system. In this project, we designed a questionnaire-based pedigree-drawing software program named “f-treeGC”, which enables even less-experienced medical practitioners to accurately and rapidly collect genealogical information and create pedigree charts, in full compliance with international standards [2].

Implementation

Programming

f-treeGC is written in ActionScript 3.0, and may be run on Adobe AIR, which is a cross-platform runtime system.

Operating environment

f-treeGC is supported by both Windows (Windows 7, 8, and 10) and Macintosh (operating system (OS) X). Adobe AIR Runtime [5] must be installed before installation and use of f-treeGC, and Adobe Reader DC [6] is required for the printing function. Via these programs, the f-treeGC air file may be opened to install the software. The f-treeGC software program is available for use, at no monetary cost, at the Iwate Medical University Hospital website (http://www.iwate-med.ac.jp/hospital/clinics/medical/m26/).

Results

The method for the creation of pedigree charts is described in the following sections.

Confirmation of whether or not the client has a child

At system startup, the client is prompted to provide required information on the presence or absence of children (Additional file 1a). f-treeGC is capable of creating a pedigree that includes three generations (Fig. 1a). Couples with offspring are included in the 2nd generation of the family tree (Fig. 2a, Additional file 2), whereas clients with no children are included in the 3rd generation (Figs. 1a and 2b, Additional file 3). A representative correspondence table is shown in Table 1.
Fig. 1

Information entry screen of f-treeGC; information for three generations is required to create the pedigree (a). The genealogical information requested includes name (b, u), age (c, d), gender, general status [affected (i, j, k), asymptomatic/presymptomatic carrier, carrier, or deceased], infertility status, pregnancy status, fetal status, and disease status (m, n, o, p, q, t) of individuals belonging to three generations. In addition, client, proband and birth order information, including multiple gestation (e, f), custody (g), multiple individuals (h), donor or surrogate, adoption, and consanguinity (l) information may be inserted. The chart-creation process is visible for inspection on the lower left side of the f-treeGC screen in real time (r). A multiple-choice questionnaire for genetic information is filled out by an interviewer or the client; then, f-treeGC automatically creates a pedigree chart (r, s, t, v, w)

Fig. 2

Fictitious pedigrees created by f-treeGC. a Fictitious ultimate pedigree, b A hypothetical pedigree representative of a family with von Hippel-Lindau syndrome shown in Fig. 1, partially modified from Bennett et al. [1, 7]. The clients are included in the 2nd generation (a) or in the 3rd generation (b) upon confirmation at system startup

Table 1

Correspondence table of f-treeGC

Client has a childClient has NO children
Client (consultand) coupleParents of client
Children of client coupleClient (consultand)
Husband’s (his) parentsPaternal grandparents
His siblingsPaternal uncles/aunts
His paternal uncles/auntsSiblings of paternal grandfather
His maternal uncles/auntsSiblings of paternal grandmother
His divorced partnersDivorced partners of father
Wife’s (her) parentsMaternal grandparents
Her siblingsMaternal uncles/aunts
Her paternal uncles/auntsSiblings of maternal grandfather
Her maternal uncles/auntsSiblings of maternal grandmother
Her divorced partnersDivorced partners of mother
Information entry screen of f-treeGC; information for three generations is required to create the pedigree (a). The genealogical information requested includes name (b, u), age (c, d), gender, general status [affected (i, j, k), asymptomatic/presymptomatic carrier, carrier, or deceased], infertility status, pregnancy status, fetal status, and disease status (m, n, o, p, q, t) of individuals belonging to three generations. In addition, client, proband and birth order information, including multiple gestation (e, f), custody (g), multiple individuals (h), donor or surrogate, adoption, and consanguinity (l) information may be inserted. The chart-creation process is visible for inspection on the lower left side of the f-treeGC screen in real time (r). A multiple-choice questionnaire for genetic information is filled out by an interviewer or the client; then, f-treeGC automatically creates a pedigree chart (r, s, t, v, w) Fictitious pedigrees created by f-treeGC. a Fictitious ultimate pedigree, b A hypothetical pedigree representative of a family with von Hippel-Lindau syndrome shown in Fig. 1, partially modified from Bennett et al. [1, 7]. The clients are included in the 2nd generation (a) or in the 3rd generation (b) upon confirmation at system startup Correspondence table of f-treeGC

Multiple-choice questionnaire

The genealogical information requested includes name, age, gender, general status (affected, asymptomatic/presymptomatic carrier, carrier, or deceased), infertility status, pregnancy status, fetal status, and health status (occurrence of any diseases) of individuals in the three generations. In addition, information regarding client and proband, as well as birth order information such as multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included (Fig. 1). By default, the “Name” field refers to the type of relationship such as father or mother. The user should delete the relationship name before inputting the relevant name (Fig. 1b). In the “Age” box (Fig. 1c) and the “Gestational age (weeks)” box (Fig. 1d), the user may select “In blank”, “? (unknown)”, or the relevant number. Inputting the same number of individuals in the “Multiple-gestation ID” (Fig. 1e) indicates multiple gestation or pregnancy with multiple fetuses. The “Monozygotic” box (Fig. 1f) is for identical twins (pregnancy). The “Custody” box (Fig. 1g) is for the position of a break in a relationship line between divorced partners, and indicates the parent(s) with primary responsibility for the children following divorce. For multiple individuals, users may select “n (unknown)” or the relevant number(s) after checking the “Multiple individuals” box (Fig. 1h). The “Affected” button of general status (Fig. 1i) is for affected individuals, and users may set a key color for the affected status in the configuration (Fig. 1j). For affected individuals with two or more conditions, the user may check for the conditions (Fig. 1k). Considering the diversity in color perception and to enable distinction in subsequent black-and-white photocopies, f-treeGC shows multiple conditions using a color of a similar shade (Additional file 1b).

A printed paper version of the questionnaire

Alternatively, family health histories may be collected using the foldable interview sheet named “f-sheet” (Fig. 3, Additional file 4), which is a printed paper version of the questionnaire in f-treeGC. The f-sheet provides an overview of genetic relationships between families according to the manner in which the sheet is folded or developed. For example, the vertical line of the folded f-sheet corresponds to the left panel of the f-treeGC (Fig. 1a). Filling out a multiple-choice questionnaire on genetic information is easier for a medical practitioner with poor digital literacy. A skilled data entry clerk may subsequently input family health histories into f-treeGC from the f-sheet as a bundle.
Fig. 3

Foldable interview sheet named “f-sheet”. a Large sheet, b gathered interview sheets for each individual, and c accordion-folded sheet. In diagram (a), the dashed-dotted lines, “-・-・-・-・-”, and broken lines, “- - - - -”, show the mountain fold and the valley fold, respectively

Foldable interview sheet named “f-sheet”. a Large sheet, b gathered interview sheets for each individual, and c accordion-folded sheet. In diagram (a), the dashed-dotted lines, “-・-・-・-・-”, and broken lines, “- - - - -”, show the mountain fold and the valley fold, respectively

Overlay function for consanguinity

With respect to consanguinity, f-treeGC shows only marriages between first cousins using the overlay function. The “Consanguinity” box should be checked and the same “Overlay ID” should be entered for this function to be effective (Figs. 1l and 4, Additional file 5).
Fig. 4

Overlay function of f-treeGC for consanguinity; a pedigree before (a) and after (d) overlay; the interview sheets of the wife (b, e) and a first cousin (c, f)

Overlay function of f-treeGC for consanguinity; a pedigree before (a) and after (d) overlay; the interview sheets of the wife (b, e) and a first cousin (c, f)

Entry fields and keys for physical features or diseases/conditions for genome cohort studies

By default, the file name automatically contains the first ten letters (Fig. 1m) that are typed into the sixteen entry fields of the “Disease, etc./KEY,” such as disease name (Fig. 1n), and for which the box is checked (Fig. 1o), to enable sorting or searching from the database. For example, the preliminary physical features entered are hair, ears, eyes, nose, philtrum, oral region, neck, hands/feet, chest, skin, abdominal, genitalia, and skeletal [7]. Diseases or conditions included in the My Family Health Portrait tool [8] include cancer, clotting disorder, dementia/Alzheimer’s disease, diabetes, gastrointestinal disorder, heart disease, high cholesterol, hypertension, kidney disease, lung disease, osteoporosis, psychological disorder, septicemia, stroke/brain attack, sudden infant death syndrome, and unknown disease (Fig. 1o). The first four out of sixteen entry fields may also be used as keys related to the multiple conditions of an affected individual (Fig. 1k, p). The “Show below symbol” box is for showing the entry below each symbol, only if the box on the left of the entry field is checked (Fig. 1q).

Pedigree chart creation

f-treeGC automatically creates a pedigree chart; the chart-creation process is visible for inspection on the screen in real time (Fig. 1r). The “Show the PEDIGREE” button (Fig. 1s) at the top of the screen displays a larger chart (Fig. 2b). The user may additionally edit a pedigree chart to visualize the larger chart with multiple displays. A context menu appears when the family tree is right-clicked. The user may select “Add comment,” right-click on the comment box, and then type the appropriate text. Holding down the left mouse button allows the comment in the family tree to be moved and placed accordingly. The user may delete the comment, if required, by selecting “Delete comment”. By default, a pedigree chart does not include the name input (Fig. 1b, t) for privacy. The user may see names by selecting “Show names” in the context menu. To print or save an image of the pedigree, including names or other health conditions, the user may capture a screen shot (Fig. 2b, Additional file 3), or input the names manually in the “Remarks” box (Figs. 1u and 2a, Additional file 2).

Saving and reading the data

The genealogical information data may be saved as the original format file (FTGC file) by clicking the “Save the FTGC DATA” button (Fig. 1v), and shared between computers that have f-treeGC installed. The created/modified date and time may be changed as necessary before saving the data (Additional file 1c). In addition, the image of the pedigree chart may be saved in PDF format by clicking the “Save an IMAGE as PDF” button (Figs. 1t and 2a). The file may be password-protected and/or saved in a read-only format (Additional file 1c). A saved file may be read by clicking the “Read the FTGC DATA” button (Fig. 1w) at the top of the screen and selecting the file.

Comparison of the pedigree symbols used

A comparison of the pedigree symbols used in f-treeGC with those of several existing tools [8-11] is shown in Table 2. f-treeGC complies fully with the international recommendations of standardized human pedigree nomenclature [2], including common pedigree symbols, pedigree lines, assisted reproductive technology symbols, and pedigree symbols of genetic evaluation/testing information (Additional file 6).
Table 2

Comparison of the pedigree symbols used

Pedigree software packagesf-treeGCPedigreeXPProgeny Free Online Pedigree ToolGenial Pedigree DrawMy Family Health Portrait
Version1.012.1.0.169Not described2.03.4
Standard pedigree symbolsa
 Name of proband/consultandYesYesYesYesNo
 Family namesYesYesYesYesYes
 HistorianYesb NoYesb NoNo
 Date of intake/updateYesNoNoNoYes
 Reason for taking pedigreeYesb NoYesb NoNo
 Ancestry of both sides of the familyYesYesYesYesNo
 AgeYesYesYesYesNo
 Generation numbered with Roman numerals I, II, III, etc.YesYesYesb Yesb No
 Individual numbered 1, 2, 3, etc.YesYesYesb Yesb No
 IndividualYesYesYesYesYes
 Affected individualYesYesYesd YesYes
 Affected individual (> one condition)Yesc Yesc,d YesYesNo
 Multiple individuals, number knownYesYesYesYesNo
 Multiple individuals, number unknownYesYesYesYesNo
 Deceased individualYesYesYesYesYes
 ConsultandYesNoNoYesNo
 ProbandYesYesd Yesd YesNo
 Stillbirth (SB)Yesb NoNoNoNo
 Pregnancy (P)YesYesYesYesNo
 Spontaneous abortion (SAB)YesYesYesd YesNo
 Affected SABYesYesYesd NoNo
 Termination of pregnancy (TOP)YesYesNoYesNo
 Affected TOPYesYesNoNoNo
 Ectopic pregnancyYesb Yesb NoYesNo
 Relationship lineYesYesYesYesYes
 A break in relationship lineYesYesYesYesNo
 Divorced partnerYese YesYesYesNo
 ConsanguinityYesYesYesYesNo
 Multiple gestation, monozygoticYesYesYesYesNo
 Multiple gestation, dizygoticYesYesYesYesNo
 Multiple gestation, unknownYesb NoYesb NoNo
 Multiple gestation, trizygoticYesYesYesYesNo
 Family history not available/known for individualYesNoNoNoNo
 No children by choice or reason unknownYesNoYesYesd No
 InfertilityYesNoYesYesd No
 AdoptionYesYesYesYesYesd
 Ovum or sperm donorYesNoNoYesNo
 Surrogate (gestational carrier)YesNoNoYesNo
 EvaluationYesb Yesb YesYesb No
 CarrierYesYesd Yesf YesNo
 Asymptomatic/presymptomatic carrierYesNoNoYesNo
 Uninformative studyYesb Yesb Yesb Yesb No
 Affected individual with positive evaluationYesb Yesb YesYesb No

aBennett et al., 2008 [2]

bBy using “Remarks”, “Comment”, “Notes”, or “Annotated Text”

cUp to four conditions

dDifferent symbols used from the recommended common pedigree symbols

eLimited to three individuals (consultand couple with children, or parents of consultand without children)

fBy using “Apply symbols”

Comparison of the pedigree symbols used aBennett et al., 2008 [2] bBy using “Remarks”, “Comment”, “Notes”, or “Annotated Text” cUp to four conditions dDifferent symbols used from the recommended common pedigree symbols eLimited to three individuals (consultand couple with children, or parents of consultand without children) fBy using “Apply symbols”

System features and functions of f-treeGC as a family history collection tool

A well-designed online family history tool from the US Surgeon General, called My Family Health Portrait, is used for the collection and storage of family history data [11, 12]. In addition, the MeTree software program developed by the Duke Center for Applied Genomics and Precision Medicine enables collection of family health history and provides clinical decision-making support for more than 30 conditions such as cancer, cardiovascular diseases, liver, and diabetes [12, 13]. The Global Alliance for Genomics and Health (GA4GH) provides the GA4GH family history collection and clinical decision support tool inventory, and is open for submission. The information collected by f-treeGC is shown in Table 3 and in Additional file 7 derived from the submission form of the GA4GH family history tools catalog [12].
Table 3

f-treeGC information

ProvenanceAcademically developed
Tool URLhttp://www.iwate-med.ac.jp/hospital/clinics/medical/m26/
Target clinical populationPrimary care and specialty
Family history information - sourceMultiple sources
Family history information - data formatBoth structured and free text
Family history information - analysisManual
Result recipientsClinician
Data storageStore in the original format file
Discrete data integration readinessApplication programing interfaces (API)
Consent documentationImplied consent only
System features - platformsWindows and Macintosh
Built in Adobe Air
System features - architectureStand-alone
System features - securityPassword security protection
Read-only mode
Standard pedigree symbolsFully compliant
Other functionsCustody
Pregnancy with twins or multiples
f-treeGC information

Verification of the software and interview sheet

To verify that f-treeGC enables users without specialized knowledge of clinical genetics and graphical skills to easily create medical pedigrees, we provided nine subjects (six nurses and three clerks) with two scenarios (D, Duchenne muscular dystrophy; P, phenylketonuria) of fictitious family histories (Additional file 8), and compared the pedigrees obtained by f-treeGC (Additional file 9) with those derived manually. The pedigrees were scored according to a system of allocation points (Additional file 8) based on the international standard [2] to examine the performance and usability of f-treeGC. The creation time was indefinite, and we divided the trees into two groups with different orders of scenarios applied. We used Windows 7 as the OS for this test. To verify that f-sheet improves the user experience for data input to f-treeGC, we provided 47 high school students from one high school (males, N = 28; females, N = 19; age range, 15–16 years; grade, the first year) with the software and data for two scenarios. Students were randomly assigned to two groups: students of one group created pedigrees for both scenarios (Additional file 8) using f-treeGC without f-sheet (group TT; males, N = 17; females, N = 6). Students of the other group first created pedigrees for scenario D using f-treeGC without f-sheet, and then created pedigrees for scenario P using f-treeGC with a completed f-sheet (group TS; males, N = 11; females, N = 13). The pedigrees with or without f-sheet were scored using our points allocation system (Additional file 8) based on the international standard [2]; then, the scores were compared to examine the efficacy and usability of f-sheet. The creation time was indefinite. The OS used for this purpose was Windows 7. The Wilcoxon signed-rank test and Mann-Whitney U-test were performed for statistical analyses, using Statcel4 software (OMS Ltd. Publishing, Saitama, Japan). Significance was set at p < 0.05. The family trees obtained using f-treeGC had higher scores than those that were manually created (p < 0.001) (Table 4). Moreover, the input time and family tree scores of trees created using f-treeGC were not affected by the difference in scenario content, order of application, or the qualifications of each user (Table 4). Furthermore, the scores of the family trees created using f-treeGC with a completed f-sheet were higher than those created using f-treeGC without f-sheet (p < 0.01) (Table 5).
Table 4

Comparison of pedigree scores and creation time for each factor

FactorsMedian (Range) P value N Statistics
Method (manual method vs. f-treeGC software)Manualf-treeGCWilcoxon signed-rank sum test
 Score (%) of both scenarios59.5(23.7)86.4(25.8)0.00019***18
 Score (%) of scenario D58.8(14.7)86.8(16.2)0.00769**9
 Score (%) of scenario P60.2(23.7)86.0(25.8)0.00742**9
Order of scenarios (D to P vs. P to D)D to PP to DMann-Whitney U-test
 Score (%) of scenario D by the manual method55.9(11.8)61.0(14.7)0.323125 × 4
 Time (sec/individuals) of scenario D by the manual method42.5(18.8)25.9(12.5)0.01390*5 × 4
 Score (%) of scenario P by the manual method60.2(11.8)57.5(23.7)1.000005 × 4
 Time (sec/individuals) of scenario P by the manual method26.7(16.3)28.8(33.3)0.325165 × 4
 Score (%) of scenario D by f-treeGC83.8(16.2)87.5(13.2)0.619805 × 4
 Time (sec/individuals) of scenario D by f-treeGC65.0(49.4)61.9(23.4)0.462435 × 4
 Score (%) of scenario P by f-treeGC86.0(25.8)87.6(8.5)1.000005 × 4
 Time (sec/individuals) of scenario P by f-treeGC46.7(25.4)51.5(44.3)0.327195 × 4
Order of scenarios (1st vs. 2nd)1st2ndWilcoxon signed-rank sum test
 Score (%) by the manual method55.9(23.7)60.3(14.7)0.441279
 Time (sec/individuals) by the manual method40.0(37.5)26.7(19.2)0.01086*9
 Score (%) by f-treeGC83.9(18.9)86.8(25.8)0.678409
 Time (sec/individuals) by f-treeGC59.2(65.6)50.4(38.5)0.138649
Qualification (nurse vs. clerk)NurseClerkMann-Whitney U-test
 Score (%) by the manual method61.0(23.7)54.1(17.2)0.1333912 × 6
 Time (sec/individuals) by the manual method30.8(40.8)26.3(45.4)0.6731012 × 6
 Score (%) by f-treeGC86.4(17.2)86.8(25.8)0.8510312 × 6
 Time (sec/individuals) by f-treeGC57.1(53.1)39.4(47.9)0.1895512 × 6

*p < 0.05

**p < 0.01

***p < 0.001

Table 5

Comparison of pedigree scores using f-treeGC with or without f-sheet

FactorsMedian (Range) P value N Statistics
Group (TT vs. TS)TTTSMann-Whitney U-test
 Score (%) of scenario D89.7(10.3)87.5(26.5)0.0196*23 × 24
 Score (%) of scenario P88.8(24.5)92.3(17.3)0.0109*23 × 24
Scenario (D vs. P)DPWilcoxon signed-rank sum test
 Score (%) of group TT89.7(10.3)88.8(24.5)0.692223
 Score (%) of group TS87.5(26.5)92.3(17.3)0.0018**24

*p < 0.05

**p < 0.01

Comparison of pedigree scores and creation time for each factor *p < 0.05 **p < 0.01 ***p < 0.001 Comparison of pedigree scores using f-treeGC with or without f-sheet *p < 0.05 **p < 0.01

Discussion

In the present study, we report the development of f-treeGC, a free stand-alone application built as a cross-platform runtime system. f-treeGC is capable of automatically creating a medical family tree compliant with international standards [2] by filling out available family tree information on a medical interview sheet (Fig. 1). Family histories are entered as both structured data and free text by the clinician or data entry clerk, and collected from patients or through f-sheet, which is a printed paper version of the questionnaire in f-treeGC (Fig. 3, Additional file 4). The family history data are stored in a computer in the original format file. f-treeGC may be used for collecting family health histories and creating pedigrees for individuals participating in situations such as primary care, genetic counseling, or genome cohort studies. The targeted clinical populations are recipients of primary and specialty health care facilities. f-treeGC simplifies the process of creating pedigrees by confirming whether the client has offspring at system startup (Table 1, Additional file 1a) and by using the overlay function for confirming consanguinity (Fig. 4). Here, we show that f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature (Table 2), is highly useful for creating pedigree charts for applications in genetic counseling. However, the present study is not without limitations. As f-treeGC is only capable of creating a pedigree up to three generations, this software is currently unsuitable for creating large pedigrees. There are no auxiliary input functions for medical terms, pedigree-overlay function, nor a calculator for determining disease risk. f-treeGC is not adapted for compliance with Health-Level 7 (HL7) standards. Although numerous health and medical conditions exist [13], f-treeGC is limited to only sixteen medical conditions per person. Low quality of family history data collected presents a challenge in pedigree analysis [14]. Before collecting family health histories, users should guide patients regarding what to inquire of relatives, as the amount and accuracy of the family history is limited. The Iwate Tohoku Medical Megabank Organization conducts genetics workshops mentored by medical geneticists or genetic counselors to highlight the importance of family health history before recruiting participants for cohort studies of the TMM project. Family history, the ultimate genetic tool [15], is the most cost-effective and well known “genetic test” in clinical practice today [16]. However, recording family trees according to standard recommendations generally requires knowledge of graphical interfaces and clinical genetics [7]. In 2016, the National Human Genome Research Institute (NHGRI) convened a Family Health History Tool Meeting at the National Institute of Health (NIH) for identifying and sharing successful approaches to using family health history tools, and for identifying unresolved issues and potential solutions that may be addressed by policy, research, and/or collaborative efforts. The removal of barriers to health equality in populations with low levels of literacy, and exploration/expansion additional technological approaches for family health history collection was discussed in this meeting [14]. Six years have passed since the Great East Japan Earthquake and Tsunami. However, health and medical services has not been fully restored to date. The TMM project initiated two prospective cohort studies in the Miyagi and Iwate prefectures, which include the disaster-stricken areas: a population-based adult cohort study, in which 80,000 participants were recruited, and a birth and three-generation cohort study, in which 70,000 participants, included fetuses and their parents, siblings, grandparents, and extended family members, were recruited [4]. Collection of significant numbers of family health histories by conventional pedigree-drawing software programs is challenging in these regions owing to the lack of good internet service and personal computers. We used f-treeGC for genetic counseling at our institution, collecting approximately 100 patient histories and corresponding data, which would have taken a genetic counselor around twenty minutes in a clinical setting. In contrast, the software took about one minute per person to input two clinical scenarios at the verification experiment (Table 4). Since the use of f-treeGC in combination with f-sheet simplifies the process of collection of many numerous health histories and pedigrees (Table 5), its application is not limited to heredity clinics, but also to large-scale genome-cohort studies that handle large amounts of genetic information obtained through interviews at a single recruiting event. The main advantages of f-treeGC are collection of several family histories for large-scale cohort studies in a short period of time, easing the burden of collection of genealogical information and creation of pedigree charts in remote medical practice by less experienced medical practitioners. In addition, the present tool facilitates online genetic counseling owing to its complete compliance with the international recommendations for standardized human pedigree nomenclature (Table 2). Public awareness regarding the basic principles of genetics should be considered for the improvement of public health. Familial/pedigree information is valuable for variant filtering in high-throughput sequencing studies [17, 18]. Molecular approaches for the identification of disease-associated genes generally begin with pedigree-based methods, including positional cloning and founder gene approaches, prior to the use of pedigree-independent methods such as candidate gene approaches and genome-wide association studies [19]. With the recent explosion in whole-genome sequencing, linkage analysis has emerged as an important and powerful analytical method for the identification of genes involved in disease etiology, often in conjunction with whole-genome sequencing filtering approaches [20]. From this perspective, f-treeGC is a useful tool, not only for facile and accurate pedigree analysis, but also for conveniently collecting numerous family histories and pedigrees simultaneously. In future, we aim to add a calculator function for determining disease risk, an auxiliary input function for medical terms, a search function for family health conditions from free text, an adaption for HL7, and a pedigree-overlay function to the present f-treeGC software.

Conclusions

The f-treeGC software enables collection of family health history and automatically creates a medical family tree simply by filling out family tree information on a medical interview sheet, or by inputting the information in the questionnaire directly from the f-sheet.

Availability and requirements

Project name: TMM project Project home page: http://www.amed.go.jp/en/program/list/04/01/042.html Operating systems: Windows and Macintosh Programing language: ActionScript 3.0 Licence: f-treeGC is a non-copylefted software, and is copyrighted by the Iwate Medical University and Holonic Systems, Ltd. The source code is not available. Dialog boxes of f-treeGC (a) Confirmation of whether or not the client has a child at system startup, (b) Configuration of the color for affected individuals, (c) File attribute setting for changing the created/modified date and time, setting a password, and converting to read-only. (PPTX 141 kb) A pedigree file of Fig. 2a; fictitious ultimate pedigree, partially modified from Bennett et al. [1, 7]. (FTGC 20 kb) A pedigree file of Fig. 2b; a hypothetical pedigree representative of a family with von Hippel-Lindau syndrome, partially modified from Bennett et al. [1, 7]. (FTGC 9 kb) f-sheet; a printed paper version of the questionnaire in f-treeGC. (XLSX 57 kb) A pedigree file of Fig. 4d; with respect to consanguinity, f-treeGC shows only marriages between first cousins using the overlay function. (FTGC 8 kb) List of symbols used in f-treeGC; f-treeGC fully complies with the international recommendations of standardized human pedigree nomenclature [2]. (PDF 8 kb) Current family history collection tools and f-treeGC; partially modified from GA4GH family history collection and clinical decision support tool inventory 6–9-16 v4.1 by Clinical Working Group of the Global Alliance for Genomics and Health. (XLSX 18 kb) Two scenarios for the creation of pedigrees; scenario D (Duchenne muscular dystrophy) and scenario P (phenylketonuria). Any resemblance to real persons and pedigrees, living or dead, is purely coincidental. (XLSX 12 kb) Model pedigrees of scenarios outlined (a) Scenario D, (b) scenario P. (PPTX 389 kb)
  8 in total

1.  Standardized human pedigree nomenclature: update and assessment of the recommendations of the National Society of Genetic Counselors.

Authors:  Robin L Bennett; Kathryn Steinhaus French; Robert G Resta; Debra Lochner Doyle
Journal:  J Genet Couns       Date:  2008-09-16       Impact factor: 2.537

Review 2.  Identifying human disease genes: advances in molecular genetics and computational approaches.

Authors:  S M Bakhtiar; A Ali; S M Baig; D Barh; A Miyoshi; V Azevedo
Journal:  Genet Mol Res       Date:  2014-07-04

Review 3.  Genetic linkage analysis in the age of whole-genome sequencing.

Authors:  Jurg Ott; Jing Wang; Suzanne M Leal
Journal:  Nat Rev Genet       Date:  2015-03-31       Impact factor: 53.242

Review 4.  The role of large pedigrees in an era of high-throughput sequencing.

Authors:  Ellen M Wijsman
Journal:  Hum Genet       Date:  2012-06-20       Impact factor: 4.132

5.  Development and validation of a primary care-based family health history and decision support program (MeTree).

Authors:  Lori A Orlando; Adam H Buchanan; Susan E Hahn; Carol A Christianson; Karen P Powell; Celette Sugg Skinner; Blair Chesnut; Colette Blach; Barbara Due; Geoffrey S Ginsburg; Vincent C Henrich
Journal:  N C Med J       Date:  2013 Jul-Aug

6.  Recommendations for standardized human pedigree nomenclature.

Authors:  R L Bennett; K A Steinhaus; S B Uhrich; C K O'Sullivan; R G Resta; D Lochner-Doyle; D S Markel; V Vincent; J Hamanishi
Journal:  J Genet Couns       Date:  1995-12       Impact factor: 2.537

Review 7.  Using familial information for variant filtering in high-throughput sequencing studies.

Authors:  Melanie Bahlo; Rick Tankard; Vesna Lukic; Karen L Oliver; Katherine R Smith
Journal:  Hum Genet       Date:  2014-08-17       Impact factor: 4.132

8.  The Tohoku Medical Megabank Project: Design and Mission.

Authors:  Shinichi Kuriyama; Nobuo Yaegashi; Fuji Nagami; Tomohiko Arai; Yoshio Kawaguchi; Noriko Osumi; Masaki Sakaida; Yoichi Suzuki; Keiko Nakayama; Hiroaki Hashizume; Gen Tamiya; Hiroshi Kawame; Kichiya Suzuki; Atsushi Hozawa; Naoki Nakaya; Masahiro Kikuya; Hirohito Metoki; Ichiro Tsuji; Nobuo Fuse; Hideyasu Kiyomoto; Junichi Sugawara; Akito Tsuboi; Shinichi Egawa; Kiyoshi Ito; Koichi Chida; Tadashi Ishii; Hiroaki Tomita; Yasuyuki Taki; Naoko Minegishi; Naoto Ishii; Jun Yasuda; Kazuhiko Igarashi; Ritsuko Shimizu; Masao Nagasaki; Seizo Koshiba; Kengo Kinoshita; Soichi Ogishima; Takako Takai-Igarashi; Teiji Tominaga; Osamu Tanabe; Noriaki Ohuchi; Toru Shimosegawa; Shigeo Kure; Hiroshi Tanaka; Sadayoshi Ito; Jiro Hitomi; Kozo Tanno; Motoyuki Nakamura; Kuniaki Ogasawara; Seiichiro Kobayashi; Kiyomi Sakata; Mamoru Satoh; Atsushi Shimizu; Makoto Sasaki; Ryujin Endo; Kenji Sobue; The Tohoku Medical Megabank Project Study Group; Masayuki Yamamoto
Journal:  J Epidemiol       Date:  2016-07-02       Impact factor: 3.211

  8 in total
  1 in total

1.  Azacitidine is a potential therapeutic drug for pyridoxine-refractory female X-linked sideroblastic anemia.

Authors:  Yuki Morimoto; Kazuhisa Chonabayashi; Hiroshi Kawabata; Chikako Okubo; Makiko Yamasaki-Morita; Misato Nishikawa; Megumi Narita; Azusa Inagaki; Kayoko Nakanishi; Miki Nagao; Akifumi Takaori-Kondo; Yoshinori Yoshida
Journal:  Blood Adv       Date:  2022-02-22
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.